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Publications

Anderson, J. R., Betts, S., & Fincham, J. M. (2026). Using the environment to predict memory performance. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication. https://dx.doi.org/10.1037/xlm0001577

Jon M. Fincham, Shawn Betts, John R. Anderson, Combining EEG signals from the 2 members of a team to improve event identification, NeuroImage: Reports, Volume 6, Issue 2, 2026, 100356, ISSN 2666-9560, https://doi.org/10.1016/j.ynirp.2026.100356.

Xu, Y., Prat, C. S., Sense, F., van Rijn, H., & Stocco, A. (2025). Default Mode Network Connectivity Predicts Individual Differences in Long-Term Forgetting: Evidence for Storage Degradation, not Retrieval Failure. PLoS Computational Biology, 21 (9): e1013485.

Schoppek, W., Emond, B. (2025). Understanding the complexity of music improvisation: Leveraging cognitive models to inform adaptive instruction design. In: Robert A. Sottilare, Jessica Schwarz (eds.), Adaptive instructional systems, 233-246. Cham: Springer.

Anderson, J.R., Betts, S., Bothell, D., Dimov, C.M. and Fincham, J.M. (2024), Tracking the Cognitive Band in an Open-Ended Task. Cognitive Science, 48: e13454. https://doi.org/10.1111/cogs.13454

Dimov, C. M., Anderson, J. R., & Betts, S. A.(2024). Tight resource-rational analysis. Cognitive Systems Research 86. https://doi.org/10.1016/j.cogsys.2024.101239

Rehman, U., Cao, S., & MacGregor, C. G. (2024). Modelling level 1 situation awareness in driving: A cognitive architecture approach. Transportation Research Part C: Emerging Technologies, 165, 104737.

Rehman, U., Cao, S., & Macgregor, C. G. (2024). Modeling Brake Perception Response Time in On-Road and Roadside Hazards Using an Integrated Cognitive Architecture. IEEE Transactions on Human-Machine Systems.

Xu, R., Cao, S., Kearns, S. K., Niechwiej-Szwedo, E., & Irving, E. (2024). Computational Cognitive Modeling of Pilot Performance in Pre-flight and Take-off Procedures. Journal of Aviation/Aerospace Education & Research, 33(4). DOI: https://doi.org/10.58940/2329- 258X.2026

Ball, J. & Rodgers, S. (2023, June). Cognitively and Linguistically Motivated Part of Speech Tagging: Quantitative Assessment of a Near Human-Scale Computational Cognitive Model. Paper presented at Virtual MathPsych/ICCM 2023. Via https://mathpsych.org/presentation/1267.

Dimov, C. M., Anderson, J. R., Betts, S. A., & Bothell, D. (2023). An Integrated Model of Collaborative Skill Acquisition: Anticipation, Control Tuning, and Role Adoption. Cognitive Science, 47:e13303. https://doi.org/10.1111/cogs.13303

Hough, A. R., Stevens, C., Fox, E. L., & Myers, C. (2023, July). An initial cognitive model of a radar detection task. Paper presented at MathPsych/ICCM/EMPG 2023. Via mathpsych.org/presentation/1103.

Stocco, A., Rice, P., Thomson, R., Smith, B. M., Morrison, D., & Lebiere, C. (2023). An Integrated Computational Framework for the Neurobiology of Memory Based on the ACT-R Declarative Memory System. Computational Brain and Behavior. https://doi.org/10.1007/s42113-023-00189-y

Fincham, J. M., Tenison, C., & Anderson, J. R. (2022, July). Combining EEG and a cognitive model to infer the time course of game play. Paper presented at Virtual MathPsych/ICCM 2022. Via mathpsych.org/presentation/728.

Anderson, J. R., Betts, S., Byrne, M. D., Schooler, L. J., & Stanley, C. (2022, December 22). The Environmental Basis of Memory. Psychological Review. Advance online publication. https://dx.doi.org/10.1037/rev0000409

Xu, Y., Stocco, A. Recovering Reliable Idiographic Biological Parameters from Noisy Behavioral Data: the Case of Basal Ganglia Indices in the Probabilistic Selection Task. Comput Brain Behav (2021). https://doi.org/10.1007/s42113-021-00102-5

Yang, Y. C., Karmol, A. M., & Stocco, A. (2021). Core Cognitive Mechanisms Underlying Syntactic Priming: A Comparison of Three Alternative Models. Frontiers in psychology, 12, 2293.

Smith, B.M., Thomasson, M., Yang, Y.C., Sibert, C., Stocco, A. (2021) When Fear Shrinks the Brain: A Computational Model of the Effects of Posttraumatic Stress on Hippocampal Volume. Topics in Cognitive Science, 13(3), 499–514

Stocco, A., Prat, C. S. Graham, L. K., & (2021). Individual differences in reward learning processes predict fluid reasoning abilities. Cognitive Science, 45(2), e12941.

Anderson, J. R., Betts, S., Bothell, D., & Lebiere, C. (2021). Discovering Skill. Cognitive Psychology, 129.

Gianferrara P.G., Betts S., Anderson J.R. (2021) Cognitive & motor skill transfer across speeds: A video game study. PLoS ONE 16(10): e0258242.

Seow, R. Y. T., Betts, S. A., & Anderson, J. R. (2021). A Decay-Based Account of Learning and Adaptation in Complex Skills. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication.

Morita, J., Miwa, K., Maehigashi, A., Terai, H., Kojima, K., and Ritter, F. E. (2020). Cognitive Modeling of Automation Adaptation in a Time Critical Task. Frontiers in Psychology (section Cognitive Science), doi: 10.3389/fpsyg.2020.02149.

Nishikawa, J., and Morita, J. (2020). Modeling The Cognitive Modeling of Errors During the Japanese Phonological Awareness Formation Process. in Proceedings of the 18th Annual Meeting of the International Conference on Cognitive Modelling.

Nagashima, K., Morita, J., and Takeuchi, Y. (2020). Modeling Intrinsic Motivation in ACT-R: Focusing on the Relation Between Pattern Matching and Intellectual Curiosity. in Proceedings of the 18th Annual Meeting of the International Conference on Cognitive Modelling.

Xu, Y. Reliable Idiographic Parameters From Noisy Behavioral Data: The Case of Individual Differences in a Reinforcement Learning Task.

Wirzberger, M., Borst, J. P., Krems, J. F., & Rey, G. D. (2020). Memory-related cognitive load effects in an interrupted learning task: A model-based explanation. Trends in Neuroscience and Education, 20, 100139. https://doi.org/10.1016/j.tine.2020.100139

Itabashi, K., Morita, J., Hirayama, T., Mase, K., and Yamada, K. (2020). Interactive Model-based Reminiscence Using a Cognitive Model and Physiological Indices. in Proceedings of the 18th International Conference on Cognitive Modelling.

Ceballos, J. M., Stocco, A., & Prat, C. S. (2020). The role of basal ganglia reinforcement learning in lexical ambiguity resolution. Topics in Cognitive Science, 12(1), 402–416.

Rice, P., & Stocco, A. (2019). The role of dorsal premotor cortex in resolving abstract motor rules: Converging evidence from Transcranial Magnetic Stimulation and cognitive modeling. Topics in Cognitive Science.

Rehman, U., Cao, S., & MacGregor, C. (2019). Using an Integrated Cognitive Architecture to Model the Effect of Environmental Complexity on Drivers’ Situation Awareness. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 63, No. 1, pp. 812-816). Sage CA: Los Angeles, CA: SAGE Publications.

Anderson, J. R., Betts, S., Fincham, J. M., Hope, R., & Walsh, M. W. (2020). Reconstructing fine-grained cognition from brain activity. NeuroImage, 221, 116999.

Anderson, J.R., Betts, S., Bothell, D., Hope, R., Lebiere, C. (2019) Learning Rapid and Precise Skills. Psychological Review, 126(5), 727-760.

Fincham, JM, Lee, HS, Anderson, JR. Spatiotemporal analysis of event‐related fMRI to reveal cognitive states. Human Brain Mapping. 2019; 1– 18. https://doi.org/10.1002/hbm.24831

Deng, C., Cao, S., Wu, C., & Lyu, N. (2019). Predicting drivers’ direction sign reading reaction time using an integrated cognitive architecture. IET Intelligent Transport Systems, 13(4), 622-627.

Deng, C., Cao, S., Wu, C., & Lyu, N. (2019). Modeling driver take-over reaction time and emergency response time using an integrated cognitive architecture. Transportation Research Record.

Zhang, Q., van Vugt, M., Borst, J.P., &amp Anderson, J.R. (2018). Mapping working memory retrieval in space and in time: A combined electroencephalography and electrocorticography approach. NeuroImage. 174. 472-484.

Zhang, Q., Walsh, M.M., &amp Anderson, J.R. (2018) The Impact of Inserting an Additional Mental Process. Computational Brain & Behavior. https://doi.org/10.1007/s42113-018-0002-8

Stocco, A. (2018). A Biologically Plausible Action Selection System for Cognitive Architectures: Implications of Basal Ganglia Anatomy for Learning and Decision‐Making Models. Cognitive science, 42(2), 457-490.

Cao, S., Ho, A., & He, J. (2018). Modeling and predicting mobile phone touchscreen transcription typing using an integrated cognitive architecture. International Journal of Human-Computer Interaction, 34(6), 544-556.

Anderson, J.R., Borst, J.P., Fincham, J.M., Ghuman, A.S., Tenison, C., & Zhang, Q. (2018). The Common Time Course of Memory Processes Revealed. Psychological Science, 29(9), 1463-1474.

Juvina, I., Larue, O., & Hough, A. (2018). Modeling valuation and core affect in a cognitive architecture: The impact of arousal and valence on memory and decision-making. Cognitive Systems Research 48: 4-24. https://dx.doi.org/10.1016/j.cogsys.2017.06.002

Ritter, F. E., Tehranchi, F., & Oury, J. D. (2018). ACT‐R: A cognitive architecture for modeling cognition. Wiley Interdisciplinary Reviews: Cognitive Science, e1488.

Tehranchi, F., & Ritter, F. E. (2018). Using Java to provide cognitive models with a universal way to interact with graphic interfaces. In The Proceedings of the International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. Washington DC, USA.

Glavan, J. J., & Houpt, J. W. (2018). An Integrated Working Memory Model for Time‐Based Resource‐Sharing. Topics in cognitive science.

Schooler, L. J., &amp Anderson, J. R. (2017). The Adaptive Nature of Memory. In J. H. Byrne (Ed.) Learning and Memory: A Comprehensive Reference, 2nd edition. Amsterdam, Elsevier.

Wirzberger, M., Rey, G. D., & Krems, J. F. (2017). Modeling cognitive load effects in an interrupted learning task: An ACT-R approach. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (pp. 3540-3545). Austin, TX: Cognitive Science Society.

Zhang, Q., Borst, J.P., ,Kass, R. E., &amp Anderson, J.R. (2017) Inter-subject Alignment of MEG Datasets in a Common Representational Space. Human Brain Mapping. 38. 4287–4301.

Koerner, F. S., Anderson, J. R., Fincham, J. M., & Kass, R. E. (2017). Change-point detection of cognitive states across multiple trials in functional neuroimaging. Statistics in Medicine, 36(4), 618-642.

Walsh, M. M., Gunzelmann, G., & Anderson, J. R. (2017). Relationship of P3b single-trial latencies and response times in one, two, and three-stimulus oddball tasks. Biological Psychology, 123, 47-61.

Pyke, A. A., Fincham, J. M., & Anderson, J. R. (2017). When math operations have visuospatial meanings versus purely symbolic definitions: Which solving stages and brain regions are affected?. NeuroImage.

Zhang, Q., Borst, J.P., Kass, R.E., & Anderson, J.R. (2017). Inter-Subject Alignment of MEG Datasets in a Common Representational Space. Human Brain Mapping 38(9), 4287-4301.

Borst, J.P. & Anderson, J.R. (2017). A Step-By-Step Tutorial on using the Cognitive Architecture ACT-R in combination with fMRI Data. Journal of Mathematical Psychology 76, pp. 94-103.

Morita, J., Konno, T., Okuda, J., Samejima, K., Li, G., Fujiwara, M., and Hashimoto, T. (2017). Implicit Memory Processing in the Formation of a Shared Communication System. in Proceedings of the 15th International Conference on Cognitive Modeling.

Stocco, A. Murray, N. L., Yamasaki, B. L., Renno, T., Nguyen, J., & Prat, C. S. (2017). Individual differences in the Simon effect are underpinned by differences in the competitive dynamics in the basal ganglia: An experimental verification and a computational model. Cognition, 164, 31-45.

Zhang, Q., Walsh, M.M., & Anderson, J.R. (2017). The Effects of Probe Similarity on Retrieval and Comparison Processes in Associative Recognition. Journal of Cognitive Neuroscience. 29(2). 352-367.

Dimov, C. M. (2017). How to implement HyGene into ACT-R. Journal of Cognitive Psychology, 1-14.

Dimov, C.M., Marewski, J. N., & Schooler, L. J. (2017). Architectural process models of decision making: Towards a model database. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (pp. 1931-1936). Austin, TX: Cognitive Science Society.

Dimov, C. M., Link, D. (2017). Do People Order Cues by Retrieval Fluency when Making Probabilistic Inferences? Journal of Behavioral Decision Making, 30, 843–854.

Arslan, B., Taatgen, N., & Verbrugge, R. (2017). Five-year-olds’ systematic errors in second-order false belief tasks are due to first-order theory of mind strategy selection: A computational modeling study. Frontiers in Psychology, 8:275.

Lee, H. S., Betts, S. & Anderson, J. R. (2017). Embellishing Problem-Solving Examples with Deep Structure Information Facilitates Transfer. The Journal of Experimental Education, 85(2),309-333.

Dörr, L.-M., Russwinkel, N. and Prezenski, S. (2016). ACT-Droid: ACT-R interacting with Android applications. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling. University Park, PA: Penn State.

Anderson, J. R., Pyke, A., & Fincham, J. M. (2016). Hidden Stages of Cognition Revealed in Patterns of Brain Activation. Psychological Science, 27(9), 1215-1226.

Tenison, C., Fincham, J.M., & Anderson, J.R. (2016). Phases of Learning: How Skill Acquisition Impacts Cognitive Processing. Cognitive Psychology, 87, 1-28.

Pirolli. P. (2016). A computational cognitive model of self-efficacy and daily adherence in mHealth. Translational Behavioral Medicine, 1- 13. doi:10.1007/s13142-016-0391-y

Anderson, J.R., Zhang, Q., Borst, J.P., & Walsh, M.M. (2016). The Discovery of Processing Stages: Extension of Sternberg’s Method. Psychological Review, 123(5), 481-509.

Wirzberger, M., & Rey, G. D. (2016). Examining load-inducing factors in instructional design: An ACT-R approach. In D. Reitter, & F. E. Ritter (Eds.). Proceedings of the 14th International Conference on Cognitive Modeling (ICCM 2016) (pp. 223-224). University Park, PA: Penn State.

Anderson, J.R., Bothell, D., Fincham, J.M., & Moon, J. (2016). The Sequential Structure of Brain Activation Predicts Skill. Neuropsychologia, 81, 94-106.

Borst, J.P., Ghuman, A.S., & Anderson, J.R. (2016). Tracking Cognitive Processing Stages with MEG: A Spatio-Temporal Model of Associative Recognition in the Brain. NeuroImage 141, pp. 416-430.

Prezenski, S. and Russwinkel, N. (2016). Towards a general model of repeated app usage. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling. University Park, PA: Penn State.

Lee, H.S., Betts, S. & Anderson,J.R. (2016) Learning Problem-Solving Rules as Search Through a Hypothesis Space. Cognitive Science, 40(5), 1036-1079.

Nijboer, M., Borst, J.P., Van Rijn, H., & Taatgen, N.A. (2016). Contrasting Single and Multi-Component Working-Memory Systems in Dual Tasking. Cognitive Psychology 86, 1-26.

Halbrügge, M., & Russwinkel, N. (2016). The sum of two models: How a composite model explains unexpected user behavior in a dual-task scenario. In D. Reitter & F. E. Ritter (eds.), Proceedings of the 14th international conference on cognitive modeling (pp. 137–143). University Park, PA: Penn State.

Halbrügge, M., Quade, M. & Engelbrecht, K.-P. (2016). Cognitive Strategies in HCI and Their Implications on User Error. In A. Papafragou, D. Grodner, D. Mirman, & J. C. Trueswell (eds.), Proceedings of the 38th annual meeting of the Cognitive Science Society (pp. 2549–2554). Austin, TX: Cognitive Science Society.

Borst, J.P. & Anderson, J.R. (2015). Using the ACT-R Cognitive Architecture in combination with fMRI data. In B.U. Forstmann, & E.-J. Wagenmakers (Eds.), An Introduction to Model-Based Cognitive Neuroscience. Springer: New York.

Tenison, C., & Anderson, J. R. (2015, November 9). Modeling the Distinct Phases of Skill Acquisition. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication. https://dx.doi.org/10.1037/xlm0000204

Moon,J., Fincham,J.M., Betts,S.A., & Anderson,J.R.,(2015). End effects and cross-dimensional interference in identification of time and length: Evidence for a common memory mechanism. Cognitive, Affective, & Behavioral Neuroscience, 15, 680-695.

Borst, J.P., Nijboer, M., Taatgen, N.A., Van Rijn, H., & Anderson, J.R. (2015). Using Data-Driven Model-Brain Mappings to Constrain Formal Models of Cognition. PLoS ONE 10(3): e0119673.

Cao, S., Qin, Y., Zhao, L., & Shen, M. (2015). Modeling the development of vehicle lateral control skills in a cognitive architecture. Transportation Research Part F: Traffic Psychology and Behaviour, 32, 1-10.

Halbrügge, M., Quade, M. & Engelbrecht, K.-P. (2015). A Predictive Model of Human Error based on User Interface Development Models and a Cognitive Architecture. In Taatgen, N. A.; van Vugt, M. K.; Borst, J. P. & Mehlhorn, K. (Eds.) Proceedings of the 13th International Conference on Cognitive Modeling, 238-243, Groningen: University of Groningen,

Wirzberger, M., & Russwinkel, N. (2015). Modeling interruption and resumption in a smartphone task: An ACT-R approach. i- com, 14(2), 147-154. doi:10.1515/icom-2015-0033

Lebiere, C., Bothell, D., Morrison, D., Oltramari, A., Romero, O., Thomson, R., & Vinokurov, J. (2015). Strong CogSci: Guidance from Cognitive Science On the Design of a Test of Artificial Intelligence. In Rossi, F (Ed), Beyond The Turing Test Workshop Proceedings of the 29th AAAI Conference. Austin, TX.

Lebiere, C., Bennati, S., Thomson, R., Shakarian, P., & Nunes, E. (2015). Functional Cognitive Models of Malware Identification. In N. Taatgen (Ed), Proceedings of the 13th Annual Conference on Cognitive Modeling. Groningen, Netherlands.

Thomson, R. Lebiere, C., Bennati, S., Shakarian, P., & Nunes, E. (2015). Malware Identification Using Cognitively-Inspired Inference. In Proceedings of the 24th Annual Behavior Representation in Modeling and Simulation Conference. Washington, DC.

Thomson, R., Pyke, A., Trafton, J. G., & Hiatt, L. M. (2015). An Account of Associative Learning in Memory Recall. In Proceedings of the 37th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Thomson, R., Lebiere, C., Anderson, J. R., & Staszewski, J. (2015). A General Instance-Based Learning Framework for Studying Intuitive Decision Making in a Cognitive Architecture. Journal of Applied Research in Memory and Cognition; Special Issue on Modeling and Aiding Intuitions in Organizational Decision Making.

Borst, J.P. & Anderson, J.R. (2015). The Discovery of Processing Stages: Analyzing EEG data with Hidden Semi-Markov Models. NeuroImage 108, 60-73.

Cao, S., & Liu, Y. (2015). Modelling workload in cognitive and concurrent tasks with time stress using an integrated cognitive architecture. International Journal of Human Factors Modelling and Simulation, 5(2), 113–135. https://doi.org/10.1504/IJHFMS.2015.075360

Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2015). What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption. In Proceedings CHI 2015. Seoul, Korea.

Lee, H. S., Fincham, J. M., & Anderson, J. R. (2015). Learning from examples versus verbal directions in mathematical problem solving. Mind, Brain, and Education, 9(4), 232-245.

Halbrügge, M., Quade, M., & Engelbrecht, K.-P. (2015) How can Cognitive Modeling Benefit from Ontologies? Evidence from the HCI Domain. In Bieger, J., Goertzel, B., & Potapov, A. (Eds.) Proceedings of Artificial General Intelligence 2015, pp. 261–271. Berlin: Springer.

Anderson, J. R., Lee, H. S., & Fincham, J. M. (2014). Discovering the structure of mathematical problem solving. NeuroImage, 97, 163-177.

Marewski, J. N., & Link, D. (2014). Strategy selection: An introduction to the modeling challenge. Wiley Interdisciplinary Reviews: Cognitive Science, 5, 39-59. DOI: 10.1002/wcs.1265

Tenison, C., Fincham, J. M., & Anderson, J. R. (2014). Detecting math problem solving strategies: An investigation into the use of retrospective self-reports, latency and fMRI data. Neuropsychologia, 54, 41-52.

Gartenberg, D., Veksler, B., Gunzelmann, G., & Trafton, J. G. (2014).  An ACT-R process model of the signal duration phenomenon of vigilance. In Proceedings of 58th annual meeting of the Human Factors and Ergonomics Society.

Cao, S., Qin, Y., Jin, X., Zhao, L., & Shen, M. (2014). Effect of driving experience on collision avoidance braking: An experimental investigation and computational modelling. Behaviour and Information Technology, 33(9), 929–940.

Anderson, J. R. & Fincham, J. M. (2014). Extending Problem-Solving Procedures. Cognitive Psychology, Nov;74:1-31.

Peebles, D. & Jones, C. (2014). A model of object location memory. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Thomson, R. Lebiere, C., & Bennati, S. (2014). Human, Model, and Machine: A Complementary Approach to Big Data. In Association for Computing Machinery Proceedings of the IARPA Workshop on Human Centered Big Data Research. Raleigh, NC. doi:10.1145/2609876.2609883

Thomson, R. Lebiere, C., & Bennati, S. (2014). A General Instance-Based Model of Sensemaking in a Functional Architecture. In Proceedings of the 23rd Annual Behavior Representation in Modeling and Simulation Conference. Washington, DC.

Thomson, R., Bennati, S., & Lebiere, C. (2014). Extending the Influence of Contextual Information in ACT-R using Buffer Decay. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Pyke, A., Betts, S., Fincham, J. M., & Anderson, J. R. (2014). Visuospatial referents facilitate the learning and transfer of mathematical operations: Extending the role of the angular gyrus. Cognitive, Affective, & Behavioral Neuroscience, 1-22.

Lee, H. S., Fincham, J. M., Betts, S. & Anderson, J. R. (2014). An fMRI investigation of instructional guidance in mathematical problem solving. Trends in Neuroscience and Education, 3(2), 50–62.

Moon, J., & Anderson, J. R. (2013). Timing in multitasking: Memory contamination and time pressure bias. Cognitive Psychology, 67 (1/2), 26-54.

Walsh, M. M., & Anderson, J. R. (2013). Navigating complex decision spaces: Problems and paradigms in sequential choice. Psychological Bulletin, .

Anderson, J. R. & Fincham, J. M. (2013). Discovering the sequential structure of thought. Cognitive Science, 37(6), 1-31.

Lee, H. S., Betts, S. & Anderson, J. R. (under review). Revealing hidden structure by explicit rule-instruction versus scaffolded example.

Veksler, V. D., Gray, W. D., & Schoelles, M. S. (submitted). Goal-Proximity Decision Making. Cognitive Science.

Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2013). Can neural imaging be used to investigate learning in an educational task? In J. Stazewski (Ed.) Expertise and skill acquisition: The impact of William G. Chase (pp. 299-324). Taylor and Francis: New York.

Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2013). Validating Models of Complex, Real-Life Tasks Using fMRI. In A. Johnson & R.W. Proctor (Eds.), Neuroergonomics: A Cognitive Neuroscience Approach to Human Factors and Ergonomics. Palgrave MacMillan.

Borst, J.P., Buwalda, T.A., Van Rijn, H., & Taatgen, N.A. (2013). Avoiding the Problem State Bottleneck by Strategic use of the Environment. Acta Psychologica 144(2), 373-379.

Borst, J.P., Schneider, D.W., Walsh, M.M., & Anderson, J.R. (2013). Stages of Processing in Associative Recognition: Evidence from Behavior, Electroencephalography, and Classification. Journal of Cognitive Neuroscience, 25(12), 2151-2166.

Lee, H. S. & Anderson, J. R. (2013). Student learning: What has instruction got to do with it? Annual Review of Psychology, 64, 445-469.

Borst, J. P., & Anderson, J. R. (2013). Using model-based functional MRI to locate working memory updates and declarative memory retrievals in the fronto-parietal network. Proceedings of the National Academy of Sciences U.S.A., 110(5), 1628-1633.

Nijboer, M., Taatgen, N.A., Brands, A., Borst, J.P., & Van Rijn, H. (2013). Decision Making in Concurrent Multitasking: Do People Adapt to Task Interference? PLoS ONE 8(11), e79583.

Borst, J. & Anderson, J., R, (2013). Discovering Processing Stages by combining EEG with Hidden Markov Models. In Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Walsh, M. M., & Anderson, J. R. (2013). Electrophysiological responses to feedback during the application of abstract rules. Journal of Cognitive Neuroscience, 25(11), 1986-2002.

Moon, J., Betts, S. A., & Anderson, J. R. (2013). Individual differences and workload effects on strategy adoption in a dynamic task. Acta Psychologica, 144(1), 154-165.

Ball, J. (2013). The Advantages of ACT-R over Prolog for Natural Language Analysis. In B. Kennedy, D. Reitter & R. St. Amant (eds), Proceedings of the 22nd Annual Conference on Behavior Representation in Modeling and Simulation, 1-8. Ottowa, Canada: BRIMS Society.

Ball, J. (2013). Modeling the Binding of Implicit Arguments in Complement Clauses in ACT-R/Double-R. In R. West & T. Stewart (eds.), Proceedings of the 12th International Conference on Cognitive Modeling, 84-88. Ottawa: Carleton University.

Dimov, C., Marewski, J. N., & Schooler, L. J. (2013). Constraining ACT-R models of decision strategies: An experimental paradigm. In Knauff M., Pauen M., Sebanz N. & Wachsmuth I. (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 2201-2206). Austin, TX: Cognitive Science Society.

Borst, J.P., Nijboer, M., Taatgen, N.A., & Anderson, J.R. (2013). A Data-Driven Mapping of Five ACT-R Modules on the Brain. In R. West & T. Stewart (Eds.), Proceedings of the 12th International Conference on Cognitive Modeling. Ottawa: Carleton University.

Nijboer, M., Borst, J.P., van Rijn, H., & Taatgen, N.A. (2013). Predicting Interference in Concurrent Multitasking. In R. West & T. Stewart (Eds.), Proceedings of the 12th International Conference on Cognitive Modeling. Ottawa: Carleton University.

Cao, S. (2013). Queueing Network Modeling of Human Performance in Complex Cognitive Multi-task Scenarios (Doctoral dissertation).

Das, A., & Stuerzlinger, W. (2013). Unified Modeling of Proactive Interference and Memorization Effort: A new mathematical perspective within ACT-R theory. In Knauff M., Pauen M., Sebanz N., & Wachsmuth I. (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 358-363). Austin, TX: Cognitive Science Society.

Peebles, D. J. (2013). Strategy and pattern recognition in expert comprehension of 2 x 2 interaction graphs. Cognitive Systems Research 24 , 43–51.

Jackson, M. L., Gunzelmann, G., Whitney, P., Hinson, J. M., Belenky, G., Rabat, A., & Van Dongen, H. P. A. (2013). Deconstructing and reconstructing cognitive performance in sleep deprivation. Sleep Medicine Reviews, 17, 215-225. (DOI: 10.1016/j.smrv.2012.06.007)

Moore, L. R., & Gunzelmann, G. (2013). Task artifacts and strategic adaptation in the change signal task. Cognitive Systems Research, 24(1), 35-42. (DOI: 10.1016/j.cogsys.2012.12.001)

Moore, L. R., & Gunzelmann, G. (2013). The impact of sleep loss on time estimation: Reconciling conflicting results through modeling. In R. West & T. Stewart, Proceedings of the 12th International Conference on Cognitive Modeling (pp. 191-196). Ottawa, Canada: Carleton University.

Gluck, K. A., & Gunzelmann, G. (2013). Computational process modeling and cognitive stressors: Background and prospects for application in cognitive engineering. In J. D. Lee & A. Kirlik, The Oxford Handbook of Cognitive Engineering (pp. 424-432). New York, NY: Oxford University Press.

Gunzelmann, G. (2013). Motivations and goals in developing integrative models of human cognition [Workshop Organizer]. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society (pp. 30-31). Austin, TX: Cognitive Science Society.

Spiliopoulos, L. (2013). Beyond fictitious play beliefs: Incorporating pattern recognition and similarity matching. Games and Economic Behavior,81, 69­85.

Spiliopoulos, L. (2013). Strategic adaptation of humans playing computer algorithms in a repeated constant-sum game. Journal of Autonomous Agents and Multi-Agent Systems, 27(1), 131­160.

Dancy, C. L., & Kaulakis, R. (2013). Towards Adding Bottom-Up Homeostatic Affect to ACT-R. In R. West & T. Stewart, Proceedings of the 12th International Conference on Cognitive Modeling (pp. 316-321). Ottawa: Carleton University.

Arslan, B., Taatgen, N., Verbrugge, R. (2013). Modeling Developmental Transitions in Reasoning about False Beliefs of Others. In R. West & T. Stewart (eds.), Proceedings of the 12th International Conference on Cognitive Modeling, Ottawa: Carleton University.

Halbrügge, M. (2013). ACT-CV: Bridging the Gap between Cognitive Models and the Outer World. In Brandenburg, E., Doria, L., Gross, A., Güntzler, T., and Smieszek, H., eds., Grundlagen und Anwendungen der Mensch-Technik- Interaktion. 10. Berliner Werkstatt Mensch-Maschine-Systeme, pages 205-210, Berlin, Universitätsverlag der TU Berlin

Process models of cognition, written in architectures such as ACT-R and EPIC, should be able to interact with the same software with which human subjects interact. By eliminating the need to simulate the experiment, this approach would simplify the modeler’s effort, while ensuring that all steps required of the human are also required by the model. In practice, the difficulties of allowing one software system to interact with another present a significant barrier to any modeler who is not also skilled at this type of programming. The barrier increases if the programming language used by the modeling software differs from that used by the experimental software. The JSON Network Interface simplifies this problem for ACT-R modelers, and potentially, modelers using other systems.

Dancy, C. L. (2013). “ACT-RΦ: A cognitive architecture with physiology and affect.” Biologically Inspired Cognitive Architectures 6: 40–45.

Thomson, R. & Lebiere, C. (2013). A Balanced Hebbian Algorithm for Associative Learning in ACT-R. R. West & T. Stewart (Eds.) Proceedings of the 12th International Conference on Cognitive Modeling. Ottawa: Canada.

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Paik, J., Pirolli, P., Dong, W., Lebiere, C., & Thomson, R. (2013). An ACT-R Model of Sensemaking in a Geospatial Intelligence Task. In Proceedings of the 22nd Annual Conference on Behavior Representation in Modeling and Simulation.

Cao, S., & Liu, Y. (2013). Queueing network- adaptive control of thought rational (QN-ACTR): An integrated cognitive architecture for modelling complex cognitive and multi-task performance. International Journal of Human Factors Modelling and Simulation, 4(1), 63–86.

Wintermute, S., Betts, S. A., Ferris, J. L., Fincham, J. M., & Anderson, J. R. (2012). Brain Networks Supporting Execution of Mathematical Skills versus Acquisition of New Mathematical Competence. Public Library of Science (PLOS) ONE.

Moon, J., & Anderson, J. R. (2012). Modeling Millisecond Time Interval Estimation in Space Fortress Game. In Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 767-772). Sapporo, Japan.

Gunzelmann, G., & Moore, L. R. (2012). Evaluating the relationship between neuropsychological function and cognitive performance. In N. Miyake, R. Cooper, and D. Peebles (Eds.). Proceedings of the Thirty-Fourth Annual Meeting of the Cognitive Science Society (pp. 414-419). Austin, TX: Cognitive Science Society.

Oltramari, A. & Lebiere, C. (2012). Pursuing Artificial General Intelligence By Leveraging the Knowledge Capabilities Of ACT-R. In Proceedings of the Fifth Conference on Artificial General Intelligence (AGI 2011). Oxford, England, Oxford, December 8-11.

Oltramari, A. & Lebiere, C. (2012). Using Ontologies in a Cognitive-Grounded System: Automatic Action Recognition in Video Surveillance. In Proceedings of the Seventh International Conference on Semantic Technology for Intelligence, Defense, and Security. Fairfax, Virginia, USA.

Petrov, A. (2011). Category rating is based on prototypes and not instances: Evidence from feedback-dependent context effects. Journal of Experimental Psychology: Human Perception and Performance.

Gunzelmann, G., Moore, L. R., Salvucci, D. D., & Gluck, K. A. (2011). Sleep loss and driver performance: Quantitative predictions with zero free parameters. Cognitive Systems Research, 12(2), 154-163.

Gunzelmann, G., Gluck, K. A., Moore, L. R., & Dinges, D. F. (2012). Impaired performance due to sleep deprivation: A role for diminished knowledge access. Cognitive Systems Research, 13(1), 1-11.

Moore, L., Gunzelmann, G., & Daigle, M. (2012). One model, two tasks: Decomposing the change signal task. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Stocco, A., Lebiere, C., O’Reilly, R. C., & Anderson, J. R. (2012). Distinct contributions of the caudate nucleus, rostral prefrontal cortex, and parietal cortex to the execution of instructed tasks. Cognitive, Affective, & Behavioral Neuroscience, 12, 611-628.

Drewitz, U. & Brandenburg, S. (2012). Memory and Contextual Change in Causal Learning. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Brüssow, S., Frorath, M., Ragni, M., & Fangmeier, T. (2012). An ACT-R approach to reasoning about spatial relations with preferred and alternative mental models. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Kottlors, J., Brand, D., & Ragni, M. (2012). Modeling behavioral of attention-deficit-disorder patients in a N-back task. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Haring, K., Ragni, M., & Konieczny, L. (2012). A cognitive model of drivers attention. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Borst, J. & Anderson, J., R, (2012). Towards pinpointing the neural correlates of ACT-R: A conjunction of two model-based fMRI analyses. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Nijboer, M., Taatgen. N., van Rijn, H. (2012). Choices, choices: Task selection preference during concurrent multitasking. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

van Vugt, M. (2012). Relation ACT-R buffer activation to EEG activity during an attentional blink task. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Cao, S. & Liu, Y. (2012). ACTR-QN: Integration queueing network and ACT-R cognitive architectures. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Nyamsuren, E. & Taatgen, N. (2012). Pre-attentive and attentive vision module. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Lende, L. K. & Taatgen, N. (2012). Modeling representation shifts in learning the number line. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Bennati, S. & Ragni, M. (2012). In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Janssen, C., Howes, A., & Brumby, D. (2012) Towards optimal payoff manipulations. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Ball, J. (2012). Explorations in ACT-R based language analysis – Memory chunk activation, retrieval and verification without inhibition. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Beckmann, M., Yilmaz, U., Pöhler, G., & Wegerich, A. (2012). A framework for task accomplishment using an ACT-R simulation. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Liao, Q. V., Pirolli, P., & Fu. W.-T. (2012). An ACT-R model of credibility judgment of micro-blogging web pages.In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

van Rij. J., van Rijn, H., & Hendriks, P. (2012). How WM load influences pronoun interpretation. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Schoelles, M. & Gray, W. (2012). SimPilot: An exploration of modeling a highly interactive task with delayed feedback in a multitasking environment. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Orendain, A. O. & Wood, S. (2012). An account of cognitive flexibility and inflexibility for a complex dynamic task. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Emond, B. & Comeau, G. (2012). Cognitive modelling of early music reading skill acquisition for piano. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Peebles, D. (2012). A cognitive architecture-based model of graph comprehnsion. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Kennedy, W.G., Ritter, F. E., Juvina, I., Gratch, J. & Young, R. M. (2012). ICCM Symposium on Cognitive Modeling of Processes “Beyond Rational” In Proceedings of the 11th International Conference on Cognitive Modeling (ICCM). Berlin, Germany. 12-15 April 2012.

Altmann, E. M. & Schunn, C. D. (2012). Decay versus Interference: A new look at an old interaction. Psychological Science, 23 (11), 1435-1437.

Kennedy, W.G. & Patterson, R.E. (2012) Modeling Intuitive Decision Making in ACT-R. In Proceedings of the 11th International Conference on Cognitive Modeling (ICCM). Berlin, Germany. 12-15 April 2012.

Dancy, C. L., Ritter, F. E., & Berry, K. (2012). Towards adding a physiological substrate to ACT-R. In Proceedings of the 21st Conference on Behavior Representation in Modeling and Simulation, 78-85. Amelia Island, FL.

Janssen, C.P. & Gray, W.D. (2012) When, What, and How Much to Reward in Reinforcement Learning based Models of Cognition. Accepted for Cognitive Science, 36(2), 333-358.

Anderson, J. R., Fincham, J. M., Schneider, D. W., & Yang, J. (2012). Using brain imaging to track problem-solving in a complex state space. NeuroImage, 60, 633-643.

Schneider, D. W., & Anderson, J. R. (2012). Modeling fan effects on the time course of associative recognition. Cognitive Psychology, 64, 127-160.

Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2012). Tracking children’s mental states while solving algebra equations. Human Brain Mapping . 33(11), 2650-65.

Anderson, J. R., Betts, S. A., Ferris, J. L., Fincham, & J. M., Yang, J. (2012). Using Brain Imaging to Track Student Problem solving.IEEE Intelligent Systems, 60, 633-643.

Anderson, J. R. (2012). Tracking problem solving by multivariate pattern analysis and hidden markov model algorithms. Neuropsychologia, 50, 487-498.

Walsh, M. M. & Anderson, J. R. (2012). Learning from experience: Event-related potential correlates of reward processing, neural adaptation, and behavioral choice. Neuroscience and Biobehavioral Reviews, 36, 1870-1894.

Banks, A. (2012). The Influence of Activation Level on Belief Bias in Relational Reasoning. Cognitive Science, 37(3), 544-577.

Deline S. & Juhel J. (2012). Cognitive modeling of different processing modes in task switching: towards an explanation of the effects of aging on switching cost. In N. Rußwinkel, U. Drewitz, & H. van Rijn (Eds.), Proceedings of ICCM 2012, 11th international Conference on Cognitive Modeling (pp. 281-282). Universitätsbibliothek, Berlin.

Lende, L. K. & Taatgen, N. (2012). Modeling representation shifts in learning the number line. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.

Thomson, R., Lebiere, C., Rutledge-Taylor, M., Staszewski, J., & Anderson, J. R. (2012). Understanding Sensemaking Using Functional Architectures. In T. Jambrowski (Ed.) Proceedings of the 21st Annual Behavior Representation in Modeling and Simulation Conference. Dayton, OH.

Rutledge-Taylor, M., Lebiere, C., Thomson, R., Staszewski, J., & Anderson, J. R. (2012). A Comparison of Rule-Based versus Exemplar-Based Categorization Using the ACT-R Architecture. In Proceedings of the 21st Annual Behavior Representation in Modeling and Simulation Conference.

Dutta S., Basu A. (2012) A Cognitive Approach to Word Sense Disambiguation. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg

Halverson, T., & Gunzelmann, G. (2011). Visual Search Versus Memory in a Paired Associate Task. In Proceedings of the Human Factors and Ergonomics Society 55th Annual Meeting (pp. 875-879). Thousand Oaks, CA: SAGE. (DOI: 10.1177/1071181311551182)

Moon, J., Bothell, D., & Anderson, J. R. (2011). Using a Cognitive Model to Provide Instruction for a Dynamic Task. In Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp.2283-2288). Boston, MA.

Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2011). Using a Symbolic Process Model as input for Model-Based fMRI Analysis: Locating the Neural Correlates of Problem State Replacements. NeuroImage, 58(1), 137-147.

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Marewski, J. N., Pohl, R.F., & Vitouch, O. (2011). Recognition-based judgments and decisions: What we have learned (so far). Judgment and Decision Making, 6, 359–380

Tomlinson, T., Marewski, J. N., & Dougherty, M. R. (2011). Four challenges for cognitive research on the recognition heuristic and a call for a research strategy shift. Judgment and Decision Making, 6, 89-99.

Marewski, J. N., & Schooler, L. J. (2011). Cognitive Niches: An ecological model of strategy selection. Psychological Review, 118, 393-437.

Mehlhorn, K., & Marewski, J. N. (2011). Using a cognitive architecture to specify and test process models of decision making. Proceedings of the Interdisciplinary Workshop on Cognitive Neuroscience, Educational Research and Cognitive Modeling. Delmenhorst, Germany.

Anderson, J. R., Bothell, D., Fincham, J. M., Anderson, A. R., Poole, B. & Qin, Y. (2011). Brain Regions Engaged by Part- and Whole-task Performance in a Video Game: A Model-based Test of the Decomposition Hypothesis. Journal of Cognitive Neuroscience, 23, 3983-3997.

Kennedy, W.G. and Trafton, J.G. (2011) How long is a moment: The perception and reality of task-related absences. International Journal of Social Robotics 3(3), pp 243-252.

Möbus, C., Lenk, J. C., Özyurt, J., Thiel, C. M., & Claassen, A. (2011). Checking the ACT-R/Brain Mapping Hypothesis with a complex task: Using fMRI and Bayesian identification in a multi-dimensional strategy space. Cognitive Systems Research, In Press, Date accepted 24 Nov. 2010, Corrected Proof, available online 6 Jan 2011.

Del Missier, F. & Crescentini, C. (2011). Executive control of retrieval in noun and verb generation. Cognitive Systems Research, 12(1), 45-55.

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Walsh, M. M. & Anderson, J. R. (2011) Modulation of the feedback-related negativity by instruction and experience. Proceedings of the National Academy of Science U.S.A, 108 (47), 19048-19053.

Mehlhorn, K. & Marewski, J. N. (2011). Racing for the city: The recognition heuristic and compensatory alternatives. In L. Carlson, C. Hölscher, & T. Shipley (Eds.), Proceedings of the 33st Annual Conference of the Cognitive Science Society (pp. 360-365). Austin, TX: Cognitive Science Society.

Lenk, J. C., Möbus, C., Özyurt, J. Margarete, C., & Claassen, A. (2011). From fMRI Data To Cognitive Models: Testing the ACT-R Brain Mapping Hypothesis with an Ex-Post Model. In The Third International Conference on Advanced Cognitive Technologies and Applications (pp. 13-18). Rome, Italy.

Marewski, J. N., & Mehlhorn, K. (2011). Using the ACT-R architecture to specify 39 quantitative process models of decision making. Judgment and Decision Making, 6, 439-519.

Danker, J. F., Fincham, J. M., & Anderson, J. R. (2011). The neural correlates of competition during memory retrieval are modulated by attention to the cues. Neuropsychologia, 49, 2427-2438.

Lee, H. S., Betts, S. A. & Anderson, J. R. (2011). How can we design effective instructions to promote transfer? paper to be presented at the annual meetings of the Society for Research on Educational Effectiveness (SREE), September 8-11, 2011, Washington, D.C.

Anderson, J. R.,Betts, S. A., Ferris, J. L., & Fincham, J. M. (2011). Cognitive and metacognitive activity in mathematical problem solving: Prefrontal and parietal patterns.Cognitive, Affective, and Behavioral Neuroscience, 11, 52-67.

Lenk, J.C., Möbus, C., Özyurt, J., Thiel, C.M., & Claassen, A. (2011). How to Assess ACT-R Models Predicting BOLD Curves for a Complex Problem, In J. Özyurt, A. Anschütz, S. Bernholt, J. Lenk (eds.), Interdisciplinary Perspectives on Cognition, Education and the Brain, Hanse Studies, Vol. 7, Hanse-Wissenschaftskolleg (HWK), (pp.219-228)Institute for Advanced Study, Oldenburg: BIS-Publisher.

Anschütz, A., Bernholt, S., Özyurt, J., Lenk, J., Moschner, B., Parchmann, I., Möbus, C., & Thiel, C.M. (2011). Impact of Affective and Informative Feedback on Learning in Children before and after a Reattribution Training An Integrated Approach using Neuroimaging, Educational Research, and Modelling. In J. Özyurt, A. Anschütz, S. Bernholt, & J. Lenk (eds.), Interdisciplinary Perspectives on Cognition, Education and the Brain, Hanse Studies, Vol. 7, Hanse-Wissenschaftskolleg (HWK)(pp. 25-35), Institute for Advanced Study: Oldenburg: BIS-Publisher.

Reitter, D.& Lebiere, C. (2001). Towards cognitive models of communication and group intelligence. In Proceedings of the 33rd Annual Meeting of the Cognitive Science Society (pp.734-739). Boston, MA, July 2011.

Reitter, D., Keller, F., Moore, J. D. (2011).A computational cognitive model of syntactic priming.Cognitive Science, 35(4), 587-637.

Buwalda, T.A., Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2011). Evading a Multitasking Bottleneck: Presenting Intermediate Representations in the Environment. In Proceedings of the 33st Annual Conference of the Cognitive Science Society. Cognitive Science Society.

Kim, Sung-youn. (2011). A Model of Political Information-Processing and the Emergence of Cooperation in the Repeated Prisoner’s Dilemma. Journal of Theoretical Politics.

Kim, Sung-youn. (2011). A Model of Political Judgment: An Agent-based Simulation of Candidate Evaluation. Journal of Artificial Societies and Social Simulation, 14 (2).

Reitter, D. & Lebiere, C. (2011). How groups develop a specialized domain vocabulary: A cognitive multi-agent model. Cognitive Systems Research, 12, 175-185.

Schneider, D. W., & Anderson, J. R. (2011). A memory-based model of Hick’s law. Cognitive Psychology, 62, 193–222.

Lyon, D. R., & Gunzelmann, G. (2011). Functional equivalence and spatial path memory. Quarterly Journal of Experimental Psychology, 64(11), 2081-2087. (DOI: 10.1080/17470218.2011.618227)

Gunzelmann, G. (2011). Introduction to the Topic on Modeling Spatial Cognition. Topics in Cognitive Science, 3(4), 628-631. (DOI: 10.1111/j.1756-8765.2011.01160.x)

Gunzelmann, G., & Lyon, D. R. (2011). Representations and processes of human spatial competence. Topics in Cognitive Science, 3(4), 741-759. (DOI: 10.1111/j.1756-8765.2011.01153.x)

Lee, H. S., Anderson, A., Betts, S., & Anderson, J. R. (2011). When does provision of instruction promote learning? In L. Carlson, C. Hoelscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 3518-3523). Austin, TX: Cognitive Science Society.

Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M (2011). Using Brain imaging to interpret student problem solving. In IEEE Intelligent Systems, 26(5), 22-29.

Lebiere, C. & Anderson. J. R. (2011). Cognitive constraints on decision making under uncertainty. Frontiers in Cognition: Psychology.

Mehlhorn, K., Taatgen, N.A., Lebiere, C., & Krems, J.F. (2011). Memory Activation and the Availability of Explanations in Sequential Diagnostic Reasoning. Journal of Experimental Psychology: Learning, Memory, & Cognition, 37, 1391-1411.

Ball, J. (2011). A Pseudo-Deterministic Model of Human Language Processing. In L. Carlson, C. Hölscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 495-500. Austin, TX: Cognitive Science Society.

Russwinkel, N., Urbas, L. and Thüring, M. (2011). Predicting temporal errors in complex task environments: A computational and experimental approach. Cognitive Systems Research, 12(3-4), 336-354.

Gunzelmann, G., Moore, L. R., Gluck, K. A., Van Dongen, H. P. A., & Dinges, D. F. (2010). Fatigue in sustained attention: Generalizing mechanisms for time awake to time on task. In P. L. Ackerman (Ed.), Cognitive Fatigue: Multidisciplinary Perspectives on Current Research and Future Applications (pp. 83-96). Washington, DC: American Psychological Association.

Gunzelmann, G. & Mohebbi, R. (2010). Spatial Encoding in Briefly Presented Schematic Displays. In Poster Book: Association for Psychological Science 22nd Annual Convention. (p. 179). Washington, DC: Association for Psychological Science.

West, R., Pyke, A., Rutledge-Taylor, M. & Lang, H. (2010). Interference and ACT-R: New evidence from the fan effect. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 211-216). Philadelphia, PA: Drexel University.

Marewski, J. N., Schooler, L. J., & Gigerenzer, G. (2010). Five principles for studying people’s use of heuristics. Acta Psychologica Sinica, 42, 72-87

Marewski, J. N. (2010). On the theoretical precision, and strategy selection problem of a single-strategy approach: A comment on Glöckner, Betsch, and Schindler. Journal of Behavioral Decision Making, 23, 463-467

Teo, L. & John, B. E. (2010). The evolution of a goal-directed exploration model: Effects of information scent and go-back utility on successful exploration. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 253-258). Philadelphia, PA: Drexel University.

Möbus, C., Lenk, J. C., Claassen, A., Özyurt, J., & Thiel, C. (2010). Checking the Brain Mapping Hypothesis: Predicting and Validating BOLD Curves for a Complex Task Using ACT-R. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 163-168). Philadelphia, PA: Drexel University.

Marewski, J. N., Gaissmaier, W., Schooler, L. J., Goldstein, D. G., & Gigerenzer, G. (2010). From Recognition to Decisions: Extending and Testing Recognition-Based Models for Multi-Alternative Inference. Psychonomic Bulletin & Review, 17, 287-309.

Kennedy, W. G. & Bugajska, M. (2010). Integrating fast and slow cognitive processes. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 121-126). Philadelphia, PA: Drexel University.

Reitter, D. (2010). Metacognition and multiple strategies in a cognitive model of online control. Journal of Artificial General Intelligence, 2(2), 20-37.

Stocco, A., Lebiere, C., & Anderson, J. R. (2010). Conditional routing of information to the cortex: A model of the basal ganglia’s role in cognitive coordination. Psychological Review, 117(2), 540-574.

Danker, J. F. & Anderson, J. R. (2010). The ghosts of brain states past: Remembering reactivates the brain regions engaged during encoding. Psychological Bulletin, 136, 87-102.

Janssen, C.P. & Brumby, D.P. (2010). Strategic Adaptation to Performance Objectives in a Dual-Task Setting. Cognitive Science, 34(8), 1548+1560.

West, R. L., Pyke, A. A., Rutledge-Taylor, M. F., & Lang, H. (2010). Interference and ACT-R: New evidence from the fan effect. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 277-281). Philadelphia, PA: Drexel University.

Kim, Sung-youn, Taber, C., & Lodge, M. (2010). A model of citizens as motivated reasoner: Modeling the 2000 Presidential Election. Political Behavior 32(1).

Gluck, K. A., Stanley, C. T., Moore, L. R., Reitter, D., & Halbrugge, M. (2010). Exploration for understanding in cognitive modeling. Journal of Artificial General Intelligence,2(2), 88-107.

Myers, C., Gluck, K. A., Gunzelmann, G., & Krusmark, M. (2010). Validating computational cognitive process models across multiple timescales. Journal of Artificial General Intelligence, 2(2), 108-127.

Ball, J., Freiman, M., Rodgers, S., & Myers, C. (2010). Toward a Functional Model of Human Language Processing. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Freiman, M. & Ball, J. (2010). Improving the reading rate of double-r language. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 67-72). Philadelphia, PA: Drexel University.

Ball, J., Myers, C., Heiberg, A., Cooke, N.J., Matessa, M., Freiman, M., Rodgers, S. (2010). The synthetic teammate project. Computational and Mathematical Organization Theory, 16(3), 271-299.

Peebles, D. & Banks, A. (2010). Modelling dynamic decision making with the ACT-R cognitive architecture. Journal of Artificial General Intelligence, 2(5), 52-68.

Fincham, J.M., Anderson, J.R., Betts, S.A., & Ferris, J.L. (2010). Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System. In Proceedings of the Third International Conference on Educational Data Mining (EDM2010). Pittsburgh, PA.

Stocco, A., Lebiere, C., O’Reilly, R. C., & Anderson, J. R. (2010). The role of the anterior prefrontal-basal ganglia circuit as a biological instruction interpreter. In A. V. Samsonovich, K. R. Jóhannsdóttir, A. Chella, & B. Goertzel (Eds.) Biologically Inspired Cognitive Architectures 2010. Frontiers in Artificial Intelligence and Applications, (pp. 153-162). Amsterdam, The Netherlands: IOS Press.

Moon. M. J. & Fu, W.-T.(2010). Adaptive Information Indexing in Re-finding Information. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Das, A. & Stuerzlinger, W. (2010). Proactive interference in location learning: A new closed-form approximation. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 37-42). Philadelphia, PA: Drexel University.

Reitter, D. & Lebiere, C. (2010). Accountable modeling in ACT-UP, a sclable, rapid-prototyping ACT-R implementation. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 199-204). Philadelphia, PA: Drexel University.

Reitter, D. & Lebiere, C. (2010). A cognitive model of spatial path planning. Computational and Mathematical Organization Theory, 16(3):220-245.

Büttner, P. (2010). “Hello Java”: Linking ACT-R 6 with a Java Simulation. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 289-290). Philadelphia, PA: Drexel University.

Stanley, C. T. (2010). LETF: A Lisp-Based Exploratory Testing Framework for Computational Cognitive Models. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 297-298). Philadelphia, PA: Drexel University.

Smolen, T. & Chuderski, A. (2010). Modeling strategies in Stroop with a general architecture of executive control. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 931-936). Austin, TX: Cognitive Science Society.

Lindsey, R., Lewis, O., Pashler, H., & Mozer, M. (2010). Predicting Students’ Retention of Facts from Feedback during Study. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Napoli, A. & Fum, D. (2010). Mentalizing in games: A subtractive behavioral study of Prisoner’s Dilemma. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 338-343). Austin, TX: Cognitive Science Society.

Borst, J., Taatgen, N. A., van Rijn, H., & Stocco, A. (2010). Testing fMRI predictions of a Cognitive Model of the Problem State Multitasking Bottleneck. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

van Rij, J., van Rijn, H., & Hendriks, P. (2010). A computational model for the acquisition of referring subjects in discourse. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Brudzinski, M., Sims, C., Gray, W., & Schoelles, M. (2010). Visual Similarity is ObViS. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Matessa, M. (2010). An ACT-R List Learning Representation for Training Prediction. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Gerjets, P. & Kammerer, Y. (2010). Topical Relevance and Information Quality in Cognitive Models of Web Search Behavior: Introducing Epistemic Scent into Information Foraging Theory. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.

Harrison, A. & Trafton, J. G. (2010). Cognition for action: an architectural account for “grounded interaction”. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 246-251). Austin, TX: Cognitive Science Society.

Borst, J., Taatgen, N. A., & van Rijn, H. (2010). Locating the Neural Correlates of the Problem State Resource: Analyzing fMRI Data on the Basis of a Computational Model. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 287-288). Philadelphia, PA: Drexel University.

Guhe, M., Smaill, A., & Pease, A. (2010). Towards a cognitive model of conceptual blending. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 293-304). Philadelphia, PA: Drexel University.

van Rij, J., van Rijn, H., & Hendriks, P. (2010). A cognitive model of the acquisition and use of referring expressions. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 299-300). Philadelphia, PA: Drexel University.

Brudzinski, M. E.(2010). Contextual Memory for Goals: On the Role of Context, Attention, and Intention in Cognitive Control. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 301-302). Philadelphia, PA: Drexel University.

Janssen, C. P. (2010). Understanding strategic adaptation in multitask settings. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 309-310). Philadelphia, PA: Drexel University.

Paik, J. (2010). Exploring a Novel Training Paradigm for Knowledge and Skills Acquisition. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 319-320). Philadelphia, PA: Drexel University.

Schaffer, S. (2010). Modeling of Modality Selection in Multimodal Human-Computer Interaction. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 321-322). Philadelphia, PA: Drexel University.

Veksler, B. Z. (2010). Visual search strategies and the layout of the display. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 323-324). Philadelphia, PA: Drexel University.

van Gog, T., Kostons, D., & Paas, F. (2010). Teaching Students Self-Assessment and Task-Selection Skills with Video-Based Modeling Examples. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 296-301). Austin, TX: Cognitive Science Society.

Walsh, M. M. & Anderson, J. R. (2010). Neural correlates of temporal credit assignment. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 265-270). Philadelphia, PA: Drexel University.

van Maanen, L. & Verbrugge, R. (2010). A computational model of second-order social reasoning. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 259-564). Philadelphia, PA: Drexel University.

Rosenbloom, P. S. (2010). Combining procedural and declarative knowledge in a graphical architecture. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 205-2010). Philadelphia, PA: Drexel University.

Taatgen, N. A. & van Rijn, H. (2010). Nice Graphs, Good R2, but still a poor fit? How to be more sure your model explains your data. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 247-252). Philadelphia, PA: Drexel University.

Derbinsky, N., Laird, J. E., & Smith, B. (2010). Towards efficiently supporting large symbolic declarative memories. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 49-54). Philadelphia, PA: Drexel University.

Douglass, S. A. & Myers, C. W. (2010). Concurrent knowledge activation calculation in large declarative memories. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 55-60). Philadelphia, PA: Drexel University.

Hiatt, L. M. & Trafton, J. G. (2010). A cognitive model of theory of mind. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 91-96). Philadelphia, PA: Drexel University.

John, B. E. & Jastrzembski, T. S. (2010). Exploration of costs and benefits of predictive human performance modeling for design. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 115-120). Philadelphia, PA: Drexel University.

Napoli, A. & Fum, D. (2010). Rewards and punishments in iterated decision making: An explanation for the frequency of the contingent event effect. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 175-180). Philadelphia, PA: Drexel University.

Oliva, J., Serrano, J. S., Del Castillo, M. A., & Iglesias, Á. (2010). Cognitive modeling of the acquisition of a highly inflected verbal system. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 181-186). Philadelphia, PA: Drexel University.

Ragni, M., Fangmeier, T., & Brüssow, S. (2010). Deductive spatial reasoning: From neurological evidence to a cognitive model. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 193-198). Philadelphia, PA: Drexel University.

De Obeso Orendain, A. & Wood, S. (2010). Cognitive Modeling of Strategies in Dynamic Tasks. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 43-48). Philadelphia, PA: Drexel University.

Breslow, L. A., Harrison, A. M., & Trafton, J. G. (2010). Linguistic Spatial Gestures. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 13-18). Philadelphia, PA: Drexel University.

Paik, J., Kim, J. W., Ritter, F. E., Morgan, J. H., Haynes, S. R., & Cohen, M. A. (2010). Building large learning models with Herbal. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of ICCM Tenth International Conference on Cognitive Modeling (pp. 187-191). Philadelphia, PA.

Halverson, T., Gunzelmann, G., Moore, L. R., & Van Dongen, H. P. A. (2010). The Effects of Work Shift and Strategy on an Orientation Task. In R. Catrambone & S. Ohlsson (Eds.), Proceedings of the Thirty-Second Annual Meeting of the Cognitive Science Society (pp. 2134-2139). Austin, TX: Cognitive Science Society.

Halverson, T., Gunzelmann, G., Moore, L. R., & Van Dongen, H. P. A. (2010). Modeling the effects of work shift on learning in a mental orientation and rotation task. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 79-84). Philadelphia, PA: Drexel University.

Borst, J.P., Taatgen, N.A., Stocco, A., & Van Rijn, H. (2010). The Neural Correlates of Problem States: Testing fMRI Predictions of a Computational Model of Multitasking. PLoS ONE 5(9): e12966. doi:10.1371/journal.pone.0012966.

Anderson, J. R. (2010). Cognitive Psychology and Its Implications: Seventh Edition. New York: Worth Publishing.

Moore, L. R., Gunzelmann, G., & Brown, J. W. (2010). Modeling statistical learning and response inhibition with the change signal task. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 169-174). Philadelphia, PA: Drexel University.

Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2010). The Problem State: A Cognitive Bottleneck in Multitasking. Journal of Experimental Psychology: Learning, Memory, & Cognition, 36(2), 363-382.

Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2010). Neural imaging to track mental states while using an intelligent tutoring system. Proceedings of the National Academy of Science, 107(15), 7018-7023.

Gluck, K. A. (2010). Cognitive architectures for human factors in aviation. In E. Salas & D. Maurino (Eds.) Human Factors in Aviation, 2nd Edition (pp. 375-400). New York, NY: Elsevier.

Reitter, D., Juvina, I., Stocco, A., & Lebiere, C. (2010). Resistance is futile: Winning lemonade market share through metacognitive reasoning in a three-agent cooperative game. In Proceedings of the 19th Conference on Behavioral Representation in Modeling and Simulation (BRIMS). Charleston, S.C.

Janssen, C.P., Brumby, D.P., Dowell, J., & Chater, N. (2010). Strategic Adaptation in a Dual-Task Setting. In Proceedings of the European ACT-R Workshop 2010. Groningen, Netherlands.

Janssen, C.P., Young, R.M., Ament, G.A., Back, J., Brumby, D.P., Cox, A.L., & Grace, J. (2010). Cognitive Modelling at the UCL Interaction Centre. In Proceedings of the European ACT-R Workshop 2010. Groningen, Netherlands.

Van Maanen, L., & Van Rijn, H. (2010). The Locus of the Gratton Effect in Picture-Word Interference. Topics in Cognitive Science 2(1), 168-180.

Van Maanen, L., Van Rijn, H., Van Grootel, M., Kemna, S., Klomp, M., & Scholtens, E. (2010). Personal Publication Assistant: Abstract recommendations by a cognitive model. Cognitive Systems Research, 11(1), 120-129 (Special Issue on Brain Informatics).

Schneider, D. W., & Anderson, J. R. (2010). Asymmetric switch costs as sequential difficulty effects. Quarterly Journal of Experimental Psychology, 63, 1873–1894.

Wong, T. J., Cokely, E. T., & Schooler, L. J. (2010). An Online Database of ACT-R Parameters: Towards a Transparent Community-Based Approach to Model Development. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 282-286). Philadelphia, PA: Drexel University.

Rutledge-Taylor, M., Pyke, A., West, R. & Lang, H. (2010). Modeling a Three Term Fan Effect. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 211-216). Philadelphia, PA: Drexel University.

Halbrügge, M. (2010). Keep it simple – A case study of model development in the context of the Dynamic Stocks and Flows (DSF) task. Journal of Artificial General Intelligence, 2(2):38-51

Veksler, V. D. (2009). Second-Life as a simulation environment: Rich, high-fidelity world, minus the hassles. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 231), Manchester, United Kingdom.

Dutt, V., Yamaguchi, M., Gonzalez, C., & Proctor, R. W. (2009). In Proceedings of the 9th International Conference of Cognitive Modeling (paper 115), Manchester, United Kingdom.

Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2009). Can neural imaging investigate learning in an educational task? In proceedings of the 36th Annual Carnegie Symposium on Cognition, June 2-3, Carnegie Mellon University.

Brunstein, A., Betts, S. A., Anderson, J. R (unpublished). When minimal guidance does and does not work: Drill and kill makes discovery learning a success.

Juvina, I., & Taatgen, N. A. (2009). A repetition-suppression account of between-trial effects in a modified Stroop paradigm. Acta Psychologica, 131(1), 72-84.

Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2009). Modeling Triple-Tasking without Customized Cognitive Control. In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. Cognitive Science Society.

Salvucci, D.D., Taatgen, N.A., & Borst, J.P. (2009). Toward a Unified Theory of the Multitasking Continuum: From Concurrent Performance to Task Switching, Interruption, and Resumption. In Human Factors in Computing Systems: CHI 2009 Conference Proceedings (pp. 1819-1828). New York: ACM Press.

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Anderson, J. R., Anderson, J. F., Ferris, J. L., Fincham, J. M., & Jung, K.-J. (2009). The Lateral Inferior Prefrontal Cortex and Anterior Cingulate Cortex are Engaged at Different Stages in the Solution of Insight Problems. Proceedings of the National Academy Sciences, 106 (26), 10799-10804.

Douglass, S., Ball, J., & Rodgers, S. (2009).Large declarative memories in ACT-R. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 234), Manchester, United Kingdom.

Gunzelmann, G., Byrne, M. D., Gluck, K. A., & Moore, L. R. (2009). Using computational cognitive modeling to predict dual-task performance with sleep deprivation. Human Factors, 51(2), 251-260.

van Rijn, D. H., van Maanen, L., & van Woudenberg, M. (2009).Passing the test: Improving learning gains by balancing spacing and testing effects. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 200), Manchester, United Kingdom.

Reitter, D. & Lebiere, C. (2009). Towards explaining the evolution of domain languages with cognitive simulation. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 176), Manchester, United Kingdom.

van Maanen, L. & van Rijn D. H. (2009). The locus of the gratton effect in picture-word interference. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 187), Manchester, United Kingdom.

Borst, J. P., Taatgen, N. A., van Rijn , D. H., Stocco, A., & Fincham, J. M. (2009). Testing fMRI predictions of a dual-task interference model. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 236), Manchester, United Kingdom.

Schultheis, H. (2009). Computation and explanatory power of cognitive architectures: The case of ACT-R. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 107), Manchester, United Kingdom.

Pape, N. & Urbas, L. (2009). Testing a quantitative model of time estimation in a load-switch scenario. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 214), Manchester, United Kingdom.

Napoli, A. & Fum, D. (2009). Applying Occam’s razor to paper (and rock and scissors, too): Why simpler models are sometimes better. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 203), Manchester, United Kingdom.

Hussain, F. & Wood, S. (2009). Performance of children on the attentional network test. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 132), Manchester, United Kingdom.

Jastrzembski, T. S. & Gluck, K. A. (2009). A formal comparison of model variants for performance prediction. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 258), Manchester, United Kingdom.

Harrison, A. M. & Trafton, J. G. (2009). Gaze-following and awareness of visual perspective in chimpanzees. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 215), Manchester, United Kingdom.

Gonzalez, C., Dutt, V., Healy, A. F., Young, M. D., & Bourne, L. E., Jr. (2009). Comparison of instance and strategy models in ACT-R. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 150), Manchester, United Kingdom.

Heinath, M. (2009). High-level ACT-R modeling based on SGT task models. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 171), Manchester, United Kingdom.

Anderson, J. R., Chater, N., Schooler, L., Lewis, R. L., & Brighton, H. (2009). Rational Explanations. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 100), Manchester, United Kingdom.

Paik, J., Kim, J. W., & Ritter, F. E. (2009). A preliminary ACT-R Compiler in Herbal. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 117), Manchester, United Kingdom.

Best, B.J., Furjanic, C., Gerhart, N., Fincham, J. M., Gluck, K. A., Gunzelmann, G., Krusmark, M., (2009). Adaptive Mesh Refinement for Efficient Exploration of Cognitive Architectures and Cognitive Models. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 252), Manchester, United Kingdom.

Gluck, K. A., Gunzelmann, G.,& Krusmark, M. A. (2009). Do the details matter? Comparing performance forecasts from two computation theories of fatigue. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 172), Manchester, United Kingdom.

Gunzelmann, G., Moore, R. L., Salvucci, D. D., & Gluck, K. A. (2009). Fluctuations in alertness and sustained attention: Prediction driver performance. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 239), Manchester, United Kingdom.

Lyon, D. R. & Gunzelmann, G. (2009). Visualizing egocentric path descriptions: A computational model. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 102), Manchester, United Kingdom.

Kennedy, W.G., Bugajska, M. D., Harrison, A. M., & Trafton, J. G. (2009). “Like-Me” Simulation as an Effective and Cognitively Plausible Basis for Social Robotics. International Journal of Social Robotics, 1, 181-194.

Marewski, J. N., & Olsson, H. (2009). Beyond the null ritual: Formal modeling of psychological processes. Zeitschrift für Psychologie/Journal of Psychology, 217, 49-60.

Taatgen, N.A., Juvina, I., Schipper, M., Borst, J.P., & Martens, S. (2009). Too Much Control can Hurt: A Threaded Cognition Model of the Attentional Blink. Cognitive Psychology, 59(1), 1-29.

Pape, N., & Urbas, L. (2009). Testing a Quantitative Model of Time Estimation in a Load Switch Scenario. In A. Howes, D. Peebles, R. Cooper (Eds.), 9th International Conference on Cognitive Modeling — ICCM, Manchester, UK.

Gunzelmann, G., Gross, J. B., Gluck, K. A., & Dinges, D. F. (2009). Sleep deprivation and sustained attention performance: Integrating mathematical and cognitive modeling. Cognitive Science, 33(5), 880-910.

Van Maanen, L., Van Rijn, H., & Borst, J.P. (2009). Stroop and Picture-Word Interference are Two Sides of the Same Coin. Psychonomic Bulletin & Review, 16(6), 987-999.

Brunstein, A., Betts, S. A., & Anderson, J. R. (2009). Practice enables successful learning under minimal guidance. Journal of Educational Psychology, 101(4), 790-802.

Rosenberg-Lee, M., Lovett, M., & Anderson, J. R. (2009). Neural correlates of arithmetic calculation strategies. Cognitive, Affective, & Behavioral Neuroscience, 9(3), 270-285.

Gunzelmann, G., & Gluck, K. A. (2009). An Integrative approach to understanding and predicting the consequences of fatigue on cognitive performance. Cognitive Technology, 14(1), 14-25.

Lebiere, C. & Best, B. J. (2009). Balancing Long-Term Reinforcement and Short-Term Inhibition. In Proceedings of the 31st Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Stocco, A., Lebiere, C., & Anderson, J. R. (2009). Dopamine, learning, and production rules: The basal ganglia and the flexible control of information transfer in the brain. In A. Samsonovich (Ed.) Biologically Inspired Cognitive Architectures II (pp. 169-175), AAAI Press.

Guhe, M., Pease, A., & Smaill, A. (2009). A cognitive model of discovering commutativity. In Proceedings of the 31st Annual Conference of the Cognitive Science Society( p. 727–732).

Drewitz, U. & Thüring, M. (2009). Modeling the cofidence of predictions: A time based approach. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 222), Manchester, United Kingdom.

Chikhaoui, B., Pigot, H., Beaudoin, M., Pratte, G., Bellefeuille, P. & Laudares, F. (2009). Learning a song: an ACT-R Model. In proceedings of the International Conference on Computational Intelligence (pp. 405-410), Oslo, Norway.

Veksler, V. D., Gray, W. D., & Schoelles, M. J. (2009). Goal-Proximity Decision Making: Who needs reward anyway? In Proceedings of the 31st Annual Meeting of the Cognitive Science Society.

Böhm, U. & Mehlhorn, K. (2009). The Influence of Spreading Activation on Memory Retrieval in Sequential Diagnostic Reasoning. In Proceedings of the 9th International Conference on Cognitive Modeling. Manchester, UK.

Guhe, M. (2009). Generating referring expressions with a cognitive model. In Proceedings of PRE-CogSci 2009: Production of Referring Expressions: Bridging the gap between computational and empirical approaches to reference. 29th July 2009, Amsterdam.

Gunzelmann, G., Moore, L. R., Gluck, K. A., Van Dongen, H. P. A., & Dinges, D. F. (2009). Examining sources of individual variation in sustained attention. In N. Taatgen, & H. van Rijn (Eds.), Proceedings of the Thirty-First Annual Meeting of the Cognitive Science Society (pp. 608-613). Austin, TX: Cognitive Science Society.

Trafton, J. G., Altmann, E. M., & Ratwani, R. M. (2009). A memory for goals model o sequence errors. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 225), Manchester, United Kingdom.

Kase, S. E., Ritter, F. E., Schoelles, M. (2009). Caffeine’s effect on appraisal and mental arithmetic performance: A cognitive modeling approach tells us more. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 252), Manchester, United Kingdom.

Trafton, J. G., Harrison, A. M., Fransen, B., & Bugajska, M. (2009). An embodied model of infant gaze-following. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 216), Manchester, United Kingdom.

Ravizza, S. M., Anderson, J. R., & Carter, C. S. (2008). Errors of mathematical processing: The relationship of accuracy to neural regions associated with retrieval or representation of the problem state. Brain Research.

Salvucci, D. D., & Taatgen, N. A. (2008). Threaded cognition: An integrated theory of concurrent multitasking. Psychological Review.

Anderson, J.R., Byrne, D., Fincham, J., & Gunn, P. (2008). Role of Prefrontal and Parietal Cortices in Associative Learning. Cerebral Cortex, 18(4), 904-914.

Rosenberg-Lee, M., Lovett, M., & Anderson, J. R. (2008). Strategy variation in multi-digit mental multiplication: fMRI, behavioral and modeling perspectives. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society, San Francisco, CA, p. 72.

Fincham, J. M., Qin, Y., & Anderson, J. R. (2008). An fMRI study of cognitive demand and control during skill acquisition. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society, San Francisco, CA, p. 244.

Anderson, J.R., Fincham, J. M., Qin, Y., & Stocco, A. (2008). A Central circuit of the mind. Trends in Cognitive Science. 12(4), 136-143.

Dimperio, E., Gunzelmann, G., & Harris, J. (2008). An Initial Evaluation of a Cognitive Model of UAV Reconnaissance. In J. Hansberger (Ed.), Proceedings of the Seventeenth Conference on Behavior Representation in Modeling and Simulation (pp. 165-173). Orlando, FL: Simulation Interoperability Standards Organization.

Gunzelmann, G., & Gluck, K. A. (2008). Approaches to modeling the effects of fatigue on cognitive performance. In J. Hansberger (Ed.), Proceedings of the Seventeenth Conference on Behavior Representation in Modeling and Simulation (pp. 136-145). Orlando, FL: Simulation Interoperability Standards Organization

Best, B., Fincham, J., Gluck, K., Gunzelmann, G., & Krusmark, M. (2008). Efficient Use of Large-Scale Computational Resources. In J. Hansberger (Ed.), Proceedings of the Seventeenth Conference on Behavior Representation in Modeling and Simulation (pp. 180-181). Orlando, FL: Simulation Interoperability Standards Organization.

Van Maanen, L., & Van Rijn, H. (2008). The picture-word interference effect is a stroop effect after all. In V. Sloutsky, B. Love & K. McRae (Eds.), In proceedings of 30th Annual Meeting of the Cognitive Science Society. Washington DC.

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Pirolli, P.L., Fu, W-T., Reeder, R., & Card, S. K. (2002) A User-Tracing Architecture for Modeling Interaction with the World Wide Web. Presented at Advanced Visual Interfaces (AVI 2002), May22-24, Trento Italy.

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Emond, B. (1999). Estimating processing time of online semantic interpretation components. Proceedings of the Fifth Annual ACT-R Workshop (pp. 113-118). Fairfax, VA : Department of Psychology, George Mason University.

Belavkin, R. V., Ritter, F. E., & Elliman, D. G. (1999b). Towards including simple emotions in a cognitive architecture in order to fit children’s behaviour better. In Proceedings of the 1999 Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.

Ritter, F. E., Belavkin, R. V., & Elliman, D. G. (1999a). Affective Computing: The role of emotion in human-computer interaction. In A. Monk, A. Sasse, & A.Crerar (Eds.) Proceedings of the British HCI Group one-day meeting in conjunction with University College London.

Lebiere, C. (1999). The dynamics of cognition: An ACT-R model of cognitive arithmetic. Kognitionswissenschaft., 8 (1), pp. 5-19.

Anderson, J. R. & Reder, L. M. (1999). The size of the fan effect: Process not representation. Journal of Experimental Psychology: General, 128, 207-210.

Anderson, J. R. & Reder, L. M. (1999). The fan effect: New results and new theories. Journal of Experimental Psychology: General, 128, 186-197.

Salvucci, D. D. (1999). Mapping eye movements to cognitive processes. Doctoral Dissertation, Department of Computer Science, Carnegie Mellon University.

Lebiere, C., & West, R. L. (1999). A dynamic ACT-R model of simple games. In Proceedings of the Twenty-first Conference of the Cognitive Science Society, pp. 296-301. Mahwah, NJ: Erlbaum.

Schoppek, W. (1999). Rules and instances in the control of a static system – Modelling the influence of causal interpretation. In I. Wachsmuth & B. Jung (Eds.), KogWiss99. Sankt Augustin: Infix. (pp. 146-151).

Byrne, M. D., Anderson, J. R., Douglass, S., & Matessa, M. (1999). Eye tracking the visual search of click-down menus. Human Factors in Computing Systems: Proceedings of CHI 99, 402-409. Reading, MA: Addison Wesley.

Lerch, F. J., Gonzalez, C., & Lebiere, C. (1999). Learning under high cognitive workload. In Proceedings of the Twenty-first Conference of the Cognitive Science Society, pp. 302-307. Mahwah, NJ: Erlbaum.

Anderson, J. R., Fincham, J. M. & Douglass, S. (1999). Practice and retention: A unifying analysis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25, 1120-1136.

Altmann, E. M. & Gray, W. D. (1999). Serial attention as strategic memory. In Proceedings of the twenty-first annual conference of the Cognitive Science Society (pp. 25-30). Hillsdale, NJ: Erlbaum.

Jongman, L. & Taatgen, N. A. (1999). An ACT-R model of individual differences in changes in adaptivity due to mental fatigue (pp. 246-251). In Proceedings of the twenty-first annual conference of the cognitive science society. Mahwah, NJ: Erlbaum.

Taatgen, N. A. (1999). A model of learning task-specific knowledge for a new task. In Proceedings of the twenty-first annual conference of the Cognitive Science Society (pp. 730-735). Mahwah, NJ: Erlbaum.

Lovett, M. C., Reder, L. M., & Lebiere, C. (1999). Modeling working memory in a unified architecture: An ACT-R perspective. In A. Miyake & P. Shah (Eds.) Models of Working Memory, pp. 135-182. Cambridge, MA: Cambridge.

Taatgen, N. A. (1999). Learning without limits: from problem solving toward a unified theory of learning. Doctoral Dissertation, University of Groningen, The Netherlands.

Altmann, E. M. & Trafton, J. G. (1999). Memory for goals: An architectural perspective. In Proceedings of the twenty-first annual conference of the Cognitive Science Society (pp. 19-24). Hillsdale, NJ: Erlbaum.

Pirolli, P.L., & Card, S. K. (1999). Information foraging. Psychological Review, 106, 643-675.

Matessa, M. P. (unpublished). Communication in collaborative problem solving.

Altmann, E. M. & Gray, W. D. (1998). Pervasive episodic memory: Evidence from a control-of-attention paradigm. In M. A. Gernsbacher & S. J. Derry (Eds.), Proceedings of the twentieth annual conference of the Cognitive Science Society (pp. 42-47). Hillsdale, NJ: Erlbaum.

Wallach, D. & Tack, W. (1998). Wissenserwerb und Performanz bei der Regelung komplexer Systeme [On the relationship of learning and performance in system control]. Kognitionswissenschaft, 7, 118-123.

Anderson, J. R., Reder, L. M. & Simon, H. (1998). Radical constructivism and cognitive psychology. In D. Ravitch (Ed.) Brookings papers on education policy 1998. Washington, DC: Brookings Institute Press.

Ritter, S., Anderson, J. R., Cytrynowicz, M., & Medvedeva, O. (1998) Authoring Content in the PAT Algebra Tutor. Journal of Interactive Media in Education, 98 (9).

Wallach, D. (1998). Komplexe Regelungsprozesse: Eine kognitionswissenschaftliche Analyse [Complex system control: A cognitive science approach]. Wiesbaden: Duv.

Ritter, F. E., & Wallach, D. P. (1998). Models of two-person games in ACT-R and Soar. In Proceedings of the Second European Conference on Cognitive Modelling. 202-203. Thrumpton: Nottingham University Press.

Anderson, J. R., Bothell, D., Lebiere, C. & Matessa, M. (1998). An integrated theory of list memory. Journal of Memory and Language, 38, 341-380.

Schunn, C. D. & Anderson, J. R. (1998). Scientific discovery. In J. R. Anderson, & C. Lebiere (Eds.). The atomic components of thought, 385-428. Mahwah, NJ: Erlbaum.

Simon, T. J. (1998) Computational evidence for the foundations of numerical competence. Developmental Science, 1, 71-78.

Lebiere, C., Wallach, D. & Taatgen, N. (1998). Implicit and explicit learning in ACT-R. In F. Ritter & R. Young (Eds.). Cognitive Modeling II (pp. 183-193). Nottingham: Nottingham University Press.

Lovett, M. C. (1998). Choice. In J. R. Anderson, & C. Lebiere (Eds.). The atomic components of thought, 255-296. Mahwah, NJ: Erlbaum.

Lebiere, C. (1998). The dynamics of cognition: An ACT-R model of cognitive arithmetic. Ph.D. Dissertation. CMU Computer Science Dept Technical Report CMU-CS-98-186. Pittsburgh, PA. Available at https://reports-archive.adm.cs.cmu.edu/.

Koedinger, K. R., & Anderson, J. R. (1998). Illustrating principled design: The early evolution of a cognitive tutor for algebra symbolization. Interactive Learning Environments, 5, 161-180.

Jones, G., & Ritter, F. E. (1998). Initial explorations of modifying architectures to simulate cognitive and perceptual development. In Proceedings of the Second European Conference on Cognitive Modelling. 44-51. Nottingham: Nottingham University Press.

Jones, G., & Ritter, F. E. (1998). Simulating development by modifying architectures. In Proceedings of the Cognitive Science Society. 543-548. Madison, WI: Lawrence Erlbaum.

Salvucci, D. D. & Anderson, J. R. (1998). Tracing eye movement protocols with cognitive process models. In Proceedings of the Twentieth Annual Conference of the Cognitive Science Society, pp. 923-928. Hillsdale, NJ: Erlbaum.

Wallach, D. & Lebiere, C. (1998). Modellierung von Wissenserwerbsprozessen bei der Systemregelung [Modeling of knowledge acquisition processes in system control]. In W. Krause und U. Kottkamp (Hrsg.). Intelligente Informationsverarbeitung (pp. 93-101). Wiesbaden: Deutscher Universitätsverlag.

Murdock, J. W. , Simina, M., Davies, J., & Shippey, G. (1998). Modeling Invention by Analogy in ACT-R. In Proceedings of the Twentieth Annual Conference of the Cognitive Science Society (pp. 740-745). Mawhaw, NJ: Lawrence Erlbaum Associates.

Anderson, J. R. & Matessa, M. (1998). The rational analysis of categorization and the ACT-R architecture. In M. Oaksford & N. Chater (Eds.) Rational models of cognition, pp. 197-217. Oxford: Oxford University Press.

Anderson, J. R. & Lebiere, C. (1998). The atomic components of thought. Mahwah, NJ: Erlbaum.

Gluck, K. A., Shute, V. J., Anderson, J. R., & Lovett, M. C. (1998). Deconstructing a computer-based tutor: Striving for better learning efficiency in Stat Lady. In B. P. Goettl, H. M. Halff, C. L. Redfield, & V. J. Shute (Eds.), Proceedings of the 4th International Conference on Intelligent Tutoring Systems (pp. 66-75). New York: Springer.

Best, B. J., Schunn, C. D., & Reder, L. M. (1998). Modeling adaptivity in a dynamic task. In M. A. Gernsbacher & S. J. Derry (Eds.), Proceedings of the 20th Annual Conference of the Cognitive Science Society. (p. 144-149) Mahwah, NJ: Erlbaum.

Corbett, A. T., Koedinger, K. R., & Anderson, J. R. (1997). Intelligent tutoring systems (Chapter 37). M. G. Helander, T. K. Landauer, & P. Prabhu, (Eds.) Handbook of Human-Computer Interaction, 2nd edition. Amsterdam, The Netherlands: Elsevier Science.

Anderson, J. R., Simon, H. A., & Reder, L. M. (1997). Rejoiner: Situative versus cognitive perspectives: Form versus substance. Educational Researcher, 26, 18-21.

Matessa, M. & Anderson, J. R. (1997). Focused Learning in a Linguistic Environment. In Proceedings of the 19th Annual Conference of the Cognitive Science Society, p. 990. Mahwah, NJ: Erlbaum.

Schunn, C. D., & Anderson, J. R. (1997). General and specific expertise in scientific reasoning. In Proceedings of the 19th Annual Conference of the Cognitive Science Society, pp. 674-679. Mahwah, NJ: Erlbaum.

Anderson, J. R., Matessa, M., & Lebiere, C. (1997). ACT-R: A theory of higher level cognition and its relation to visual attention. Human Computer Interaction, 12(4), 439-462.

Anderson, J. R. & Matessa, M. P. (1997). A production system theory of serial memory. Psychological Review, 104, 728-748.

Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. (1997). Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education, 8, 30-43.

Emond, B. (1997b). Modeling natural language comprehension and anaphora resolution with ACT-R. In Proceedings of the Fourth Annual ACT-R Workshop (pp. 1-8). Pittsburgh, PA: Department of Psychology, Carnegie Mellon University.

Schooler, L. J. & Anderson, J. R. (1997). The role of process in the rational analysis of memory. Cognitive Psychology, 32(3), 219-250.

Salvucci, D. D., Anderson, J. R. & Douglass, S. (1997). Encoding and response strategies in complex skill acquisition. In Proceedings of the 19th Annual Conference of the Cognitive Science Society, pp. 1030. Mahwah, NJ: Erlbaum.

Koedinger, K. R., & MacLaren, B. A. (1997). Implicit strategies and errors in an improved model of early algebra problem solving. In Shafto, M. G. & Langley, P. (Eds.) Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society, (pp. 382-387). Hillsdale, NJ: Erlbaum.

Gluck, K. A., Lovett, M. C., & Anderson, J. R. (1997). The adaptive nature of learning from Stat Lady. In Proceedings of the 19th Annual Conference of the Cognitive Science Society, p. 931. Mahwah, NJ: Erlbaum.

Emond, B. (1997a). Cognitive processes in spreadsheet comprehension. In M. G. Shafto, & P. Langley (Eds.), Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society (pp. 908). Mahwah, NJ: Lawrence Erlbaum.

Jones, G., & Ritter, F. E. (1997). Modelling transitions in childrens’ development by starting with adults. In European Conference on Cognitive Science, 62-67. Manchester, UK.

Pirolli, P. (1997). Computational models of information scent-following in a very large browsable text collection. In Proceedings of the Conference on Human Factors in Computing, CHI 1997 (pp. 3-10). New York: ACM.

Boyland, J. T. & Anderson, J. R. (1997). Comprehension and production as avenues of syntactic priming. In Proceedings of the 19th Annual Conference of the Cognitive Science Society, p. 871. Mahwah, NJ: Erlbaum.

Blessing, S. B. (1997). A programming by demonstration authoring tool for model-tracing tutors. International Journal of Artificial Intelligence in Education, 8, 233-261

Gluck, K. A., Lovett, M. C., Anderson, J. R., & Park, J. W. (1997). Learning about learning from Stat Lady. In Proceedings of the World Conference on Educational Multimedia and Hypermedia. Charlottesville, VA: AACE.

Lee, F. J. & Anderson, J. R. (1997). Learning to Act: Acquisition and optimization of procedural skill. In Proceedings of the 19th Annual Conference of the Cognitive Science Society, pp. 418-423. Mahwah, NJ: Erlbaum.

Wallach, D. (1997). Rekonstruktion komplexer Problemlöseprozesse in einer integrativen Kognitionstheorie. [On modeling complex problem solving in an integrative theory of cognition]. In W. Krause, U. Kottkamp & R. Goertz (Hrsg.). KogWis97: Proceedings der dritten Fachtagung der Gesellschaft für Kognitionswissenschaft. Jena: Friedrich-Schiller Universität.

Anderson, J. R. & Douglass, S. (unpublished). Visual Attention and Problem Solving.

Taatgen, N. A. (1997). A rational analysis of alternating search and reflection in problem solving. In Proceedings of the 19th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Erlbaum.

Anderson, J. R., Fincham, J. M. & Douglass, S. (1997). The role of examples and rules in the acquisition of a cognitive skill. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 932-945.

Byrne, M. D. & Anderson J. A. (1997) Enhancing ACT-R’s perceptual-motor abilites. In Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society. Stanford University, p. 880. Mahwah, NJ: Erlbaum.

Lovett, M. C., Reder, L. M., & Lebiere, C. (1997). Modeling individual differences in a digit working memory task. In Proceedings of the Nineteenth Conference of the Cognitive Science Society, pp. 460-465. Mahwah, NJ: Erlbaum.

Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51, 355-365.

Anderson, J. R., Simon, H. A., & Reder, L. M. (1996). Situated learning and education. Educational Researcher, 25, 5-11.

Blessing, S. & Anderson, J. R. (1996). How people learn to skip steps. Journal of Experimental Psychology: Learning, Memory and Cognition, 22, 576-598.

Anderson, J. R. & Fincham, J. M. (1996). Categorization and sensitivity to correlation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 259-277.

Lovett, M. C. & Anderson, J. R. (1996). History of success and current context in problem solving: Combined influences on operator selection. Cognitive Psychology, 31(2), 168-217.

Anderson, J. R. (1996). Implicit memory and metacognition: Why is the glass half-full? In L. M. Reder (Ed.) Implicit memory and metacognition, 123-136. Mahwah, NJ: Erlbaum.

Anderson, J. R., Reder, L. M. & Lebiere, C. (1996). Working memory: Activation limitations on retrieval. Cognitive Psychology, 30(3), 221-256.

Harvey, L. & Anderson, J. R. (1996). Transfer of declarative knowledge in complex information processing domains. Human-Computer Interaction, 11, 69-96.

Anderson, J. R. & Sheu, C. F. (1995). Causal inference as perceptual judgments. Memory & Cognition, 23, 510-524.

Corbett, A. T. & Anderson, J. R. (1995). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4, 253-278.

Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (1995). Intelligent tutoring goes to school in the big city. In Proceedings of the 7th World Conference on Artificial Intelligence in Education, August 16-19, 1995, Washington, DC, USA.

Corbett, A. T. and Anderson, J. R. (1995). Knowledge decomposition and subgoal reification in the ACT programming tutor. Artificial Intelligence and Education, 1995: The Proceedings of AI-ED 95. Charlottesville, VA: AACE.

Anderson, J. R. (1995). Cognitive Psychology and Its Implications: Fourth Edition. New York: Freeman.

Anderson, J. R., Corbett, A. T., Koedinger, K., & Pelletier, R. (1995). Cognitive tutors: Lessons learned. The Journal of Learning Sciences, 4, 167-207.

Lee, F. J., Anderson, J. R. & Matessa, M. P. (1995). Components of Dynamic Skill Acquisition. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society (pp. 506-511). Hillsdale, NJ: Lawrence Erlbaum Associates.

Anderson, J. R. (1995). Learning and Memory. New York: Wiley.

Elliott, S. & Anderson, J. R. (1995). The effect of memory decay on predictions from changing categories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 815-836.

Corbett, A.T., Anderson, J. R., & O’Brien, A.T. (1995). Student modeling in the ACT Programming Tutor. In P. Nichols, S. Chipman and B. Brennan (eds.) Cognitively Diagnostic Assessment. (19-41). Hillsdale, NJ: Erlbaum.

Lovett, M. C. & Anderson, J. R. (1995). Making heads or tails out of selecting problem-solving strategies. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society (pp. 265-270). Hillsdale, NJ: Lawrence Erlbaum Associates.

Ritter, S. & Anderson, J. R. (1995). Calculation and strategy in the equation solving tutor. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society (pp. 413-418). Hillsdale, NJ: Lawrence Erlbaum Associates.

Anderson, J. R., John, B. E., Just, M. A., Carpenter, P. A., Kieras, D. E., & Meyer, D. E. (1995). Production system models of complex cognition. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society (pp. 9-12). Hillsdale, NJ: Lawrence Erlbaum Associates.

Anderson, J. R., Matessa, M. & Douglass, S. (1995). The ACT-R theory and visual attention. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society (pp. 61-65). Hillsdale, NJ: Lawrence Erlbaum Associates.

Anderson, J. R. & Fincham, J. M. (1994). Acquisition of Procedural skills from examples. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 1322-1340.

Lebiere, C., Anderson, J. R., & Reder, L. M. (1994). Error modeling in the ACT-R production system. In Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, 555-559. Hillsdale, NJ: Erlbaum.

Lovett, M. C. & Anderson, J. R. (1994). The effects of solving related proofs on memory and transfer in geometry problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(2), 366-378.

Corbett, A. T., Anderson, J. R., Carver, V. H. & Brancolini, S. A. (1994). Individual differences and predictive validity in student modeling. In A. Ram & K. Eiselt (Eds.) The Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Lawrence Erlbaum.

Schooler, L. J. & Anderson, J. R. (1993). Recency and Context: An Environmental Analysis of Memory. In Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society, pp. 889-894.

Corbett, A. T., Anderson J. R., & O’Brien, A. T. (1993) The predictive validity of student modeling in the ACT Programming Tutor. In P. Brna, S. Ohlsson, & H. Pain (Eds.) Artifically Intelligence and Education, 1993: The Proceedings of AI-ED 93. Charlottesville, VA: AACe.

Koedinger, K. & Anderson, J. R. (1993). Reifying implicit planning in geometry: Guidelines for model-based intelligent tutoring system design. In S. P. Lajoie & S. J. Derry (Eds.) Computers as cognitive tools (pp. 15-46). Hillsdale, NJ: Erlbaum.

Wu, Q. & Anderson, J. R. (1993). Strategy choice and change in programming. International Journal of Man and Machine, 39, 579-598.

Anderson, J. R. (1993). Rules of the Mind. Hillsdale, NJ: Erlbaum.

Anderson, J. R. (1993). Problem solving and learning. American Psychologist, 48, 35-44.

Lebiere, C. & Anderson, J. R. (1993). A Connectionist Implementation of the ACT-R Production System. In Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society, pp. 635-640.

Koedinger, K. R., & Anderson, J. R. (1993). Effective use of intelligent software in high school math classrooms. In Proceedings of the 1993 Conference on Artificial Intelligence in Education. Charlottesville, VA: AACE.

Corbett, A.T. and Anderson, J. R. (1993) Student modeling in an intelligent programming tutor. In E. Lemut, B. du Boulay & G. Dettori (Eds.) Cognitive models and intelligent environments for learning programming. New York: Springer-Verlag.

Anderson, J. R. (1992). Automaticity and the ACT* theory. American Journal of Psychology, 105, 165-180.

Anderson, J. R. & Matessa, M. (1992). Explorations of an incremental, Bayesian algorithm for categorization. Machine Learning, 9, 275-308.

Anderson, J. R. (1992). Intelligent tutoring and high school mathematics. In Proceedings of the Second International Conference on Intelligent Tutoring Systems. Montreal.

Anderson, J. R. & Corbett, A. T. (1992). Acquisition of LISP Programming Skill. In S. Chipman & A. Meyrowitz (eds.) Foundations of Knowledge Acquisition: Cognitive Models of Complex Learning. Hingham, MA: Kluwer .

Corbett, A. T. & Anderson, J. R. (1992). Student modeling and mastery learning in a computer-based programming tutor. In Proceedings of the Second International Conference on Intelligent Tutoring Systems. Montreal.

Anjaneyulu, K. S. R. & Anderson, J. R. (1992). The advantages of data flow diagrams for beginning programming. In Proceedings of the Second International Conference on Intelligent Tutoring Systems. Montreal.

Anderson, J. R., Corbett, A., Fincham, J., Hoffman, D., & Pelletier, R. (1992). General principles for an intelligent tutoring architecture. In V. Shute and W. Regian (Eds.), Cognitive Approaches to Automated Instruction, (pp. 81-106). Hillsdale, NJ: Erlbaum.

Corbett, A. T. & Anderson, J. R. (1992). The LISP intelligent tutoring system: Research in skill acquisition. In J. Larkin, R. Chabay, and C. Scheftic (Eds.), Computer Assisted Instruction and Intelligent Tutoring Systems: Establishing Communication and Collaboration. Hillsdale, NJ: Erlbaum.

Corbett, A. T., Anderson, J. R., & Fincham, J. M. (1991). Menu selection vs. typing: effects on learning in an intelligent programming tutor. In Proceedings of the International Conference of the Learning Sciences, 107-112. Evanston, IL.

Anderson, J. R. (1991). The adaptive nature of human categorization. Psychological Review, 98, 409-429.

Anderson, J. R. & Matessa, M. (1991). An iterative Bayesian algorithm for categorization. In D. Fisher, M. J. Pazzani & P. Langley (Eds.), Concept Formation: Knowledge and Experience in Unsupervised Learning. San Mateo, CA: Morgan Kaufman.

Anderson, J. R. & Pelletier, R. (1991). A development system for model-tracing tutors. In Proceedings of the International Conference of the Learning Sciences, 1-8. Evanston, IL.

Anderson, J. R. & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2, 396-408.

Wu, Q. & Anderson, J. R. (1991). Knowledge transfer among programming languages. In Proceedings of the 14th Annual Conference of the Cognitive Science Society, 376-381.

Anderson, J. R. (1991). The place of cognitive architectures in a rational analysis. In K. Van Len (Ed.), Architectures for Intelligence. Hillsdale, NJ: Erlbaum.

Koedinger, K. & Anderson, J. R. (1991) Interaction of deductive and inductive reasoning strategies in geometry novices. In Proceedings of the 14th Annual Conference of the Cognitive Science Society, 780-784.

Schooler, L. & Anderson, J. R. (1991). Does memory reflect statistical regularity in the environment? In Proceedings of the 13th Annual Conference of the Cognitive Science Society, 227-232.

Anderson, J. R. (1991). Is human cognition adaptive? Behavioral and Brain Sciences, 14, 471-484.

Singley, M. K., Anderson, J. R., & Gevins, J. S. (1991). Promoting abstract strategies in algebra word problem solving. In Proceedings of the International Conference of the Learning Sciences, 398-404. Evanston, IL.

Milson, R., Lewis, M. W., and Anderson, J. R. (1990). The TEACHER’S APPRENTICE: Building an algebra tutor (pp.53-71). In R. Freedle (Ed.), Artificial Intelligence and the Future of Testing. Hillsdale, NJ: Erlbaum.

Koedinger, K. R., & Anderson, J. R. (1990). Abstract planning and perceptual chunks: Elements of expertise in geometry. Cognitive Science, 14, 511-550.

Anderson, J. R., Boyle, C. F., Corbett, A., and Lewis, M. W. (1990) Cognitive modelling and intelligent tutoring. Artificial Intelligence, 42, 7-49.

Anderson, J. R., & Matessa, M. (1990). A rational analysis of categorization. In Proceedings of the Seventh International Machine Learning Conference, 76-84. Palo Alto, CA: Morgan Kaufman.

Anderson, J. R. (1990). Cognitive Psychology and its Implications: Third Edition. New York: Freeman.

Corbett, A. T. & Anderson, J. R. (1990). The effect of feedback control on learning to program with the LISP Tutor. In Proceedings of the Twelfth Annual Conference of the Cognitive Science Society, 796-803, Cambridge, MA.

Anderson, J. R. (1990). The Adaptive Character of Thought. Hillsdale, NJ: Erlbaum.

Servan-Schreiber, E. & Anderson, J. R. (1990). Chunking as a mechanism of implicit learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16, 592-608.

Schooler, L. J. & Anderson, J. R. (1990). The disruptive potential of immediate feedback. In Proceedings of the Twelfth Annual Conference of the Cognitive Science Society, 702-708, Cambridge, MA.

Corbett, A. T., Anderson, J. R., & Patterson, E. G., (1990). Student modelling and tutoring flexibility in the LISP Intelligent Tutoring System. In C. Frasson and G. Gauthier (Eds.) Intelligent tutoring systems: At the crossroads of artificial intelligence and education. 83-106. Norwood, NJ: Ablex.

Anderson, J. R. (1990). Analysis of student performance with the LISP tutor. In N. Fredericksen, R. Glaser, A. Lesgold, & M. Shaffo (Eds.), Diagnostic Monitoring of Skill and Knowledge Acquisition. Hillsdale, NJ: Erlbaum, 27-50.

Singley, M. K. & Anderson, J. R. (1989). Transfer of Cognitive Skill. Cambridge, MA: Harvard University Press.

Anderson, J. R. (1989). Human Memory: An Adaptive Perspective. Psychological Review, 96, 703-719.

Anderson, J. R. (1989). Practice, working memory, and the ACT* theory of skill acquisition: A Comment on Carlson, Sullivan, and Schneider. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 527-530.

Anderson, J. R., Conrad, F. G., & Corbett, A. T. (1989). Skill acquisition and the LISP Tutor. Cognitive Science, 13, 467-506.

Anderson, J. R. (1989). The analogical origins of errors in problem solving. In D. Klahr & K. Kotovsky (Eds.), 21st Carnegie Symposium on Cognition, 343-371.

Anderson, J. R. (1989). A rational analysis of human memory. In H. L. Roediger, III and F. I. M. Craik (Eds.) Varieties of Memory and Consciousness: Essays in Honor of Endel Tulving. Hillsdale, NJ: Erlbaum, 195-210.

Singley, M. K., Anderson, J. R., Gevins, J. S., & Hoffman, D. (1989). The algebra word problem tutor. Artificial Intelligence and Education, 267-275.

Anderson, J. R., & Thompson, R. (1989). Use of analogy in a production system architecture. In A. Ortony, et al. (Eds.), Similarity and Analogy, 367-397.

Anderson, J. R. & Milson, R. (1989). Human Memory: An Adaptive Perspective. Psychological Review, 96, 703-719.

Corbett, A. T., & Anderson, J. R., (1989). Feedback timing and student control in the LISP Intelligent Tutoring System. Artificial Intelligence and Education, 64-72.

Anderson, J. R. (1989). A theory of human knowledge. Artificial Intelligence, 40, 313-351.

Singley, M. K. & Anderson, J. R. (1988). A keystroke analysis of learning and transfer of text editing. Human Computer Interaction, 3, 223-274.

Katz, I. R., & Anderson J. R. (1988). Debugging: An analysis of bug-location strategies. Human Computer Interaction, 3, 351-399.

Corbett, A. T., Anderson, J. R., & Patterson, E. J. (1988). Problem compilation and tutoring flexibility in the LISP Tutor. Intelligent Tutoring Systems, 423-429.

Anderson, J. R. (1988). The expert module. In M. Polson & J. Richardson (Eds.), Handbook of Intelligent Training Systems. Hillsdale, NJ: Erlbaum, 21-53.

Anderson, J. R. (1988). The place of cognitive architectures in a rational analysis. Cognitive Science Meetings, 1-10.

Conrad, F. G. & Anderson, J. R. (1988). The process of learning LISP. Cognitive Science Meetings, 454-460.

Anderson, J. R., Pirolli, P. & Farrell, R. (1988). Learning to program recursive functions. In M. Chi, R. Glaser, & M. Farr (Eds.), The Nature of Expertise. Hillsdale, NJ: Erlbaum, 153-184.

Anderson, J. R. (1987). Methodologies for the study of human knowledge. The Behavioral and Brain Sciences, 10, 467-505.

Anderson, J. R. (1987). Skill acquisition: Compilation of weak-method problem solutions. Psychological Review, 94, 192-210.

Anderson, J. R. (1987). Causal analysis and inductive learning. In Proceedings of the Fourth International Workshop on Machine Learning. University of California, Irvine, June 22-25, 1987.

Anderson, J. R., Corbett, A. T., & Reiser, B. J. (1987). Essential LISP, Reading, MA: Addison-Wesley.

Anderson, J. R. (1987). Production systems, learning, and tutoring. In D. Klahr, P. Langley, & R. Neches (Eds.), Self-Modifying Production Systems: Models of Learning and Development. Bradford Books/MIT, Cambridge, MA.

Gray, W. D. & Anderson, J. R. (1987). Change-episodes in coding: When and how do programmers change their code? In Proceedings of the Second Conference on the Experimental Study of Programming. NJ: Able, 185-197.

McKendree, J. E., & Anderson, J. R. (1987). Frequency and practice effects on the composition of knowledge in LISP evaluation. In J. M. Carroll (Ed.), Cognitive Aspects of Human-Computer Interaction. Cambridge, Mass.: MIT Press.

Anderson, J. R., Boyle, C. F., Farrell, R., & Reiser, B. J. (1987). Cognitive principles in the design of computer tutors. In P. Morris (Ed.), Modelling Cognition, Wiley.

Jones, W. P., & Anderson, J. R. (1987). Short- and long-term memory retrieval: A comparison of the effects of information load and relatedness. Journal of Experimental Psychology: General, 116, 137-153.

Lewis, M. W., Milson, R., & Anderson, J. R. (1987). The teacher’s apprentice: Designing an intelligent authoring system for high school mathematics. In G. P. Kearsley (Ed.), Artificial Intelligence and Instruction. Reading, MA: Addison-Wesley

Anderson, J. R., & Reder, L. M. (1987). Effects of numbers of facts studied on recognition versus sensibility judgments. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 355-367.

Kessler, C., & Anderson, J. R. (1986). A model of novice debugging in LISP. In E. Soloway & S. Iyengar (Eds.), Empirical studies in programmers, Norwood, NJ: Ablex.

Anderson, J. R., & Skwarecki, E. (1986). The automated tutoring of introductory computer programming. Communications of the ACM, 29, 842-849.

Anderson, J. R., Boyle, C. F., & Yost, G. (1986) The geometry tutor. The Journal of Mathematical Behavior, 5-20.

Anderson, J. R. (1986). Knowledge compilation: The general learning mechanism. In R. Michalski, J. Carbonell, & T. Mitchell (Eds.), Machine learning II. Los Altos, CA: Morgan Kaufmann.

Kessler, C., & Anderson, J. R. (1986). Learning flow of control: Recursive and iterative procedures. Human Computer Interaction, 2, 135-166.

Anderson, J. R., Boyle, C. F., & Reiser, B. J. (1986). Intelligent tutoring systems. Electrotechnology Review, 40-41.

Singley, M. K., & Anderson, J. R. (1985). The transfer of text-editing skill. Journal of Man-Machine Interaction, 22, 403-423.

Pirolli, P. L., & Anderson, J. R. (1985). The acquisition of skill in the domain of programming recursion. Canadian Journal of Psychology, 39, 240-272.

Pirolli, P. L., & Anderson, J. R. (1985). The role of practice in fact retrieval. Journal of Experimental Psychology: Learning, Memory, & Cognition, 11, 136-153.

MacWhinney, B., & Anderson, J. R. (1985). The acquisition of grammar. In E. Gopnik (Ed.), McGill Studies in Cognitive Science, Norwood, NJ: Ablex.

Lewis, M. W., & Anderson, J. R. (1985). Discrimination of operator schemata in problem solving: Procedural learning from examples. Cognitive Psychology, 17, 26-65.

Anderson, J. R., & Jeffries, R. (1985). Novice LISP errors: Undetected losses of information from working memory. Human Computer Interaction, 1, 107-131.

Anderson, J. R., Boyle, C. F., & Yost, G. (1985). The geometry tutor. In Proceedings of IJCAI, 1-7.

Anderson, J. R. (1985). Cognitive Psychology and its Implications (2nd Ed.). New York: Freeman.

Anderson, J. R., & Reiser, B. J. (1985). The LISP tutor. Byte, 10, 159-175.

Anderson, J. R., Boyle, C. F., & Reiser, B. J. (1985). Intelligent tutoring systems. Science, 228, 456-462.

Reiser, B. J., Anderson, J. R., & Farrell, R. G. (1985). Dynamic student modelling in an intelligent tutor for LISP programming. In Proceedings of IJCAI, 8-14.

Pirolli, P. L., Anderson, J. R., & Farrell, R. (1984). Learning to program recursion. In Proceedings of the Sixth Annual Cognitive Science Meetings, 277-280.

Anderson, J. R. (1984). Cognitive psychology and intelligent tutoring. In Proceedings of the Sixth Annual Cognitive Science Meetings, 37-43.

Anderson, J. R., Farrell, R., & Sauers, R. (1984). Learning to program in LISP. Cognitive Science, 8, 87-130.

Elio, R., & Anderson, J. R. (1984). The effects of information order and learning mode on schema abstraction. Memory and Cognition, 12, 20-30.

Farrell, R., Anderson, J. R., & Reiser, B. J. (1984). Interactive student modelling in a computer-based LISP tutor. Proceedings of the Sixth Annual Cognitive Science Meetings, 252-255.

Anderson, J. R. (1984). Spreading activation. In J. R. Anderson & S. M. Kosslyn (Eds.), Essays on Learning and Memory. San Francisco, CA: Freeman.

Farrell, R., Anderson, J. R., & Reiser, B. J. (1984). An interactive computer-based tutor for LISP. Proceedings of the 1984 Meetings of AAAI.

McKendree, J., Reiser, B. J., & Anderson, J. R. (1984). Tutorial goals and strategies in the instruction of programming skills. In Proceedings of the Sixth Annual Cognitive Science Meetings, 252-254.

Anderson, J. R., Boyle, C. F., Farrell, R., & Reiser, B. J. (1984). Cognitive principles in the design of computer tutors. In Proceedings of the Sixth Annual Cognitive Science Meetings, 2-10.

Anderson, J. R., & Kosslyn, S. M. (Eds.), (1984). Essays on Learning and Memory. San Francisco, CA: Freeman

Anderson, J. R., & Pirolli, P. L. Spread of activation. (1984). Journal of Experimental Psychology: Learning, Memory, & Cognition, 10, 791-799.

Anderson, J. R. (1983). A general learning theory and its application to the acquisition of proof skills in geometry. In R. Michalski, J. Carbonell, and T. Mitchell (Eds.), Machine Learning: An Artificial Intelligence Approach. Palo Alto, CA: Tioga Publishing.

Anderson, J. R. (1983). Learning to program. In Proceedings of International Joint Conference on Artifical Intelligence, 57-62.

Anderson, J. R. (1983). Knowledge compilation: The general learning mechanisms. In Proceedings of the 1983 Machine Learning Workshop, 203-212.

Anderson, J. R. (1983). The Architecture of Cognition. Cambridge, MA: Harvard University Press.

Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behavior, 22, 261-295.

Anderson, J. R. (1983). Retrieval of information from long-term memory. Science, 220, 25-30.

Jones, W. P., & Anderson, J. R. (1982). Semantic categorization and high-speed scanning: When retrieval is faster from long-term memory than from short-term memory. Journal of Experimental Psychology: Human Learning and Memory, 8, 237-242.

Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-403.

Bradshaw, G. L., & Anderson, J. R. (1982). Elaborative encoding as an explanation of levels of processing. Journal of Verbal Learning and Verbal Behavior, 21, 165-174.

Reder, L. M., & Anderson, J. R. (1982). Effects of spacing and embellishments on memory for the main points of a text. Memory and Cognition, 10, 97-102.

Elio, R., & Anderson, J. R. (1981). The effects of category generalization and instance similarity on schema abstraction. Journal of Experimental Psychology: Human Learning and Memory, 7, 397-417.

Neves, D. M., & Anderson, J. R. (1981). Knowledge compilation: Mechanisms for the automatization of cognitive skills. In J. R. Anderson (Ed.), Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum.

Anderson, J. R. (1981). Effects of prior knowledge on memory for new information. Memory and Cognition, 9, 237-246.

Anderson, J. R. (1981). Tuning of search of the problem space for geometry proofs. In Proceedings of IJCAI-81, 97-103.

Anderson, J. R. (1981). A theory of language acquisition based on general learning principles. In Proceedings of IJCAI-81, 165-170.

Anderson, J. R. (1981). Concepts, propositions, and schemata: What are the cognitive units? In J. Flowers (Ed.), Nebraska Symposium on Motivation. Lincoln, Nebraska: University of Nebraska Press.

Anderson, J. R. (1981). Interference: The relationship between response latency and response accuracy. Journal of Experimental Psychology: Human Learning and Memory, 7, 326-343.

Anderson, J. R. (Ed.) (1981). Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum.

Anderson, J. R., Greeno, J. G., Kline, P. K., & Neves, D. M. (1981). Acquisition of problem solving skill. In J. R. Anderson (Ed.), Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum.

Ross, B. H., & Anderson, J. R. (1981). A test of parallel versus serial processing applied to memory retrieval. Journal of Mathematical Psychology, 24, 183-223.

Anderson, J. R. (1981). Memory for logical quantifiers. Journal of Verbal Learning and Verbal Behavior, 20, 306-321.

Anderson, J. R., & Ross, B. H. (1980). Evidence against a semantic-episodic distinction. Journal of Experimental Psychology: Human Learning and Memory, 6, 441-466.

Anderson, J. R. (1980). Cognitive psychology and its implications. San Francisco: Freeman.

Reder, L. M. & Anderson, J. R. (1980b). A partial resolution of the paradox of interference: the role of integrating knowledge. Cognitive Psychology, 12, 447-472.

Anderson, J. R., Kline, P. J., & Beasley, C. M. (1980). Complex learning processes. In R. Snow, P. Federico, and W. Montague (Eds.) Aptitude, learning, and instruction: Cognitive processes analyses, Volume II, 199-232. Hillsdale, NJ: Erlbaum.

Reder, L. M. & Anderson, J. R. (1980a). A comparison of texts and their summaries: memorial consequences. Journal of Verbal Learning and Verbal Behavior, 198, 121-134.

Schustack, M. W. & Anderson, J. R. (1979). Effects of analogy to prior knowledge on memory for new information. Journal of Verbal Learning and Verbal Behavior, 18, 565-584.

Anderson, J. R., Kline, P. J., & Beasley, C. M. (1979). A general learning theory and its application to schema abstraction. In G. H. Bower (Ed.) The Psychology of Learning and Motivation, New York: Academic Press.

Anderson, J. R., & Reder, L. M. (1979). An elaborative processing explanation of depth of processing. In L.S. Cermak & F.I.M. Craik (Eds.), Levels of processing in human memory. Hillsdale, NJ: Erlbaum.

Anderson, J. R. (1979). Further arguments concerning representations for mental imagery: A response to Hayes-Roth and Pylyshyn. Psychological Review, 86, 395-406.

Anderson, J. R. & Paulson, R. (1978). Interference in memory for pictorial information. Cognitive Psychology, 9, 178-202.

Anderson, J. R. (1978). Arguments concerning representations for mental imagery. Psychological Review, 85, 249-277.

Anderson, J. R. (1978). Representation of individuals in semantic nets. In Proceedings of TINLAP, 51-56.

Anderson, J. R. (1978). Computer simulation of language acquisition: A second report. In D. LaBerge and S. J. Samuels (Eds.), Perception and Comprehension. Hillsdale, NJ: Erlbaum, 1978.

Anderson, J. R. & Kline, P. (1977). Design of a Production System. In Proceedings of the Workshop on Pattern-Directed Inference Systems, 60-65.

Anderson, J. R. (1977). Induction of Augmented Transition Networks. Cognitive Science, 1, 125-157.

Anderson, J. R. (1977). Memory for information about individuals. Memory and Cognition, 5, 430-442.

Anderson, J. R. & Paulson, R. (1977). Representation and Retention of Verbatim Information. Journal of Verbal Learning and Verbal Behavior, 16, 439-451.

Anderson, J. R., Kline, P., & Lewis, C. (1977). A production system model for language processing. In P. Carpenter & M. Just (Eds.) Cognitive Processes in Comprehension, Hillsdale, NJ: Lawrence Erlbaum Associates.

Anderson, J. R. (1976). Language, memory, and thought. Hillsdale, NJ: Erlbaum.

King, D. R. W. & Anderson, J. R. (1976). Long-term memory search: An intersecting activation process. Journal of Verbal Learning and Verbal Behavior, 15, 587-605.

Lewis, C. H. & Anderson, J. R. (1976). Interference with Real World Knowledge. Cognitive Psychology, 8, 311-335.

Anderson, J. R. (1975). Review of W. Kintsch, The Representation of Meaning in memory. American Journal of Psychology, 88, 524-532.

Anderson, J. R. (1975). Item-specific and relation-specific interference in sentence memory. Journal of Experimental Psychology: Human Learning and Memory, 104, 249-260.

Anderson, J. R. (1975). Computer simulation of a language-acquisition system. In R.L. Solso (Ed.), Information Processing and Cognition: The Loyola Symposium, 295-349. Hillsdale, NJ: Lawrence Erlbaum.

Anderson, J. R. (1975). Configural properties in sentence memory: A Re-examination. Paper presented at the meeting of the Psychonomics Society.

Anderson, J. R. (1974). Verbatim and propositional representation of sentences in immediate and long-term memory. Journal of Verbal Learning and Verbal Behavior, 13, 149-162.

Anderson, J. R. (1974). Retrieval of propositional information from long-term memory. Cognitive Psychology, 5, 451-474.

Anderson, J. R. & Lewis, C. (1974). Interference with real world knowledge. Paper presented at the meeting of the Psychonomics Society.

Anderson, J. R. & Bower, G. H. (1974). A propositional theory of recognition memory. Memory and Cognition, 2, 406-412.

Anderson, J. R. (1974). Language acquisition by computer and child. Technical Report No. 55, Human Performance Center.

Anderson, J. R. & Reder, L. M. (1974). Negative judgements in and about semantic memory. Journal of Verbal Learning and Verbal Behavior, 13, 664-681.

Reder, L. M., Anderson, J. R., & Bjork, R. A. (1974). A semantic interpretation of encoding specificity. Journal of Experimental Psychology: Human Learning and Memory, 4, 648-656.

Anderson, J. R. & Hastie, R. (1974). Individuation and reference in memory: proper names and definite descriptions. Cognitive Psychology, 5, 495-514.

Anderson, J. R. & Bower, G. H. (1974). Interference in memory for multiple contexts. Memory and Cognition, 2, 509-514.

Anderson, J. R. & Bower, G. H. (1973). Human Associative memory. Washington: Winston and Sons.

Anderson, J. R. (1972) FRAN: A simulation model of free recall. In G. H. Bower, (Ed.) The Psychology of Learning and Motivation, Vol. 5. New York: Academic Press.

Anderson, J. R. A Stochastic model of sentence memory. Doctoral dissertation, Stanford University, June, 1972.

Bower, G. H., & Anderson, J. R. (1972). Recognition and retrieval processes in free recall. Psychological Review, 79, 97-123.

Anderson, J. R. & Bower, G. H. (1972). Configural properties in sentence memory. Journal of Verbal Learning and Verbal Behavior, 11, 594-605.

Anderson, J. R. & Bower, G.H. (1971). On an associative trace for sentence memory. Journal of Verbal Learning and Behavior, 10, 673-680.

Reber, A. S. & Anderson, J. R. (1970). The perception of clicks in linguistic and non-linguistic messages. Perception and Psychophysics, 8, 81-89.

Cooper, R. P. (2006). Cognitive Architectures as Lakatosian Research Programmes: Two case studies. Philosophical Psychology, 19, 199–220.

Moon, J., & Anderson, J. R. (submitted). Is temporal memory special? The choose-short effect in time and length.

Danker, J. & Anderson, J. R. (submitted). Left ventrolateral prefrontal activity during retrieval precisely reflects the difficulty of accessing information in memory. Cerebral Cortex.

Van Maanen, L., & Marewski, J. N. (2009). Recommender systems for literature selection: A competition between decision making and memory models. In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 2914-2919). Austin, TX: Cognitive Science Society.

Taatgen, N. A. & Anderson, J. R. (2009). The Past, Present, and Future of Cognitive Architectures. topiCS in Cognitive Science, 1-12.

Vasishth, S. & Lewis, R. L. (submitted). Argument-head distance and processing complexity: Explaining both locality and anti-locality effects. Language.

Kao, Y., Douglass, S. A., Fincham, J. M., Jung, K.-J., Qin, Y., & Anderson, J. R. (submitted). An information-processing approach to deconstructing a geometry proof task.

Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (submitted). Using Brain Activity to Predict When Students are Engaged in Mathematical Problem Solving. NeuroImage.