Publications in Other

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

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.

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

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

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

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

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.

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.

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.

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

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., 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.

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.

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

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.

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.

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.

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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., 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.

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. http://dx.doi.org/10.1037/xlm0000204

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.

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

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

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

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

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.

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.

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.

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

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

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.

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., 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.

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.

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.

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

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.

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.

Lebiere, C., Pirolli, P., Thomson, R., Paik, J., Rutledge-Taylor, M., Staszewski, J., & Anderson, J. (2013). A Functional Model of Sensemaking in a Neurocognitive Architecture. Computational Intelligence and Neuroscience; Special Issue on Neurocognitive Models of Sense Making.

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

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., 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., 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.

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.

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.

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.

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.

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.

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.

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., & 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.

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.

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.

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

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).

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.

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.

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.

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.

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.

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.

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.

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.

Walsh, M.M., & Anderson, J.R. (2011). Learning from delayed feedback: Neural responses in temporal credit assignment. Cognitive, Affective, and Behavioral Neuroscience, 11, 131-143.

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.

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.

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)

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

Stocco, A. & Anderson, J. R. (2008) Endogenous control and task representation: An fMRI study in algebraic problem solving. Journal of Cognitive Neuroscience, 20(7), 1300-1314.

Gunzelmann, G., Moore, L. R., Gluck, K. A., Van Dongen, H. P. A., & Dinges, D. F. (2008). Individual differences in sustained vigilant attention: Insights from computational cognitive modeling. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the Thirtieth Annual Meeting of the Cognitive Science Society (pp. 2017-2022). Austin, TX: Cognitive Science Society.

Anderson, J. R., Anderson, J. F., Ferris, J. L., Fincham, J. M., & Jung, K-J. (unpublished, 2008). Word puzzles produce distinct patterns of activation in the ventrolateral prefrontal cortex and anterior cingulate cortex.

Anderson, J. R. & Qin, Y. (2008). Using Brain Imaging to Extract the Structure of Complex Events at the Rational Time Band. Journal of Cognitive Neuroscience, 20 (9) , 1624-1636.

Gunzelmann, G., Pope, A., Wray, R., Best, B. J. & Trafton, J. G. (2008). Integrating cognitive architectures with external environments: Approaches and contributions to validation. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the Thirteenth Annual Meeting of the Cognitive Science Society (pp. 913-914). Austin, TX: Cognitive Science Society.

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.

Das, A., & Stuerzlinger, W. (2008). Modeling Learning Effects in Mobile Texting. In Proceedings of the International Conference on Mobile and Ubiquitous Multimedia: MUM 2008 (pp. 154-161). Umea, Sweden.

Anderson, J. R., Carter, C. S., Fincham, J. M., Qin,. Y., Ravizza, S. M., & Rosenberg-Lee, M. (2008). Using fMRI to Test Models of Complex Cognition. Cognitive Science, 32, 1323-1348.

Danker, J. F., Gunn, P. & Anderson, J. R. (2008). A rational account of memory predicts left prefrontal activation during controlled retrieval. Cerebral Cortex, 18, 2674-2685.

Moore, L. R., Gunzelmann, G., & Gluck, K. A. (2008). Evaluating mechanisms of fatigue using a digit symbol substitution task. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the Thirtieth Annual Meeting of the Cognitive Science Society (p. 1522). Austin, TX: Cognitive Science Society.

Juvina, I. & Taatgen, N.A. (2007). Modeling Control Strategies in the N-Back Task. In proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, Michigan, USA.

Anderson, J. R. (2007). The image of complexity. In The 29th Annual Conference of the Cognitive Science Society. Nashville, Tennessee, USA.

Heiberg, A., Harris, J., & Ball, J. T. (2007). Dynamic visualization of ACT-R declarative memory structure. In proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, Michigan, USA.

Matessa, M. P., Archer, R., & Mui, R. (2007). Dynamic spatial reasoning capability in a graphical interface evaluation tool. In proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, Michigan, USA.

Fu, W.-T. & Pirolli, P. (2007). The nature of belief inhibition in thinking: How reasoning impairs memory. In The 29th Annual Conference of the Cognitive Science Society. Nashville, Tennessee, USA.

Gunzelmann, G., Gluck, K. A., Kershner, J., Van Dongen, H. P. A., & Dinges, D. F. (2007). Understanding decrements in knowledge access resulting from increased fatigue. In The 29th Annual Conference of the Cognitive Science Society. Nashville, Tennessee, USA.

Gluck, K .A., Scheutz, M., Gunzelmann, G., Harris, J., & Kershner, J. (2007). Combinatorics meets processing power: Large-scale computational resources for BRIMS. In T. Kelley & Allender, Proceedings of the 2007 Behavior Representation in Modeling and Simulation (BRIMS) Conference (pp. 73-83). Orlando, FL: Simulation Interoperability Standards Organization.

Kronauer, R. E., Gunzelmann, G., Van Dongen, H. P. A., Doyle, F. J. III, & Klerman, E. B. (2007). Uncovering physiologic mechanisms of circadian rhythms through mathematical modeling. Journal of Biological Rhythms, 22(3), 233-245.

Gunzelmann, G., Gluck, K. A., Price, S. C., Van Dongen, H. P. A., & Dinges, D. F. (2007). Decreased arousal as a result of sleep deprivation: The unraveling of cognitive control. In W. D. Gray (Ed.), Integrated Models of Cognitive Systems (pp. 243-253). New York: Oxford University Press.

Butcher, K. R. & Aleven, V. (2007) Integrating visual and verbal knowledge during classroom learning with computer tutors. In The 29th Annual Conference of the Cognitive Science Society. Nashville, Tennessee, USA.

Juvina, I., Taatgen, N.A., & Dickison, D. (2007). Cognitive Control as Alternation of Activation and Suppression in the Stroop Task. In proceedings of the 29th Annual Conference of the Cognitive Science Society. Nashville, TN, USA.

Pavlik, P. I., Jr., Presson, N., Dozzi, G., Wu, S.-M., MacWhinney, B., & Koedinger, K. (2007). The FaCT (fact and concept) system: A new tool linking cognitive science with educators. In proceedings of the 29th Annual Conference of the Cognitive Science Society. Nashville, TN, USA.

Koedinger, K. R. & Aleven, V. (in press). Exploring the assistance dilemma in experiments with Cognitive Tutors. Educational Psychology Review.

Heinath, M., Dzaack, J., Wiesner, A. & Urbas, L. (2007). Simplifying the Development and the Analysis of Cognitive Models. In proceedings of EuroCogSci07. Delphi, Greece.

Heinath, M. & Urbas, L. (2007). Simplifying the Development of Cognitive Models using Pattern-based Modeling. In proceedings of the 10th IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design, and Evaluation of Human-Machine Systems. Seoul, Korea.

Fincham, J. M., & Anderson, J. R. (2007). An fMRI study of the neural correlates of performance and learning in an algebraic isomorph task. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society. New York, NY, p. 271

Stocco, A., & Anderson, J. R. (2007). Endogenous control in algebraic problem solving: An fMRI study. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society. New York, NY, p. 271.

Bothell, D. (2007). ACT-R 6.0 Reference Manual. From the ACT-R Web site: http://act-r.psy.cmu.edu/wordpress/wp-content/themes/ACT-R/actr6/reference-manual.pdf.

Danker, J. F. & Anderson, J. R. (2007). The roles of prefrontal and posterior parietal cortex in algebra problem-solving: A case of using cognitive modeling to inform neuroimaging data. Neuroimage, 35, 1365-1377.

Sohn, M.-H., Albert, M. V.., Stenger, V. A, Jung, K.-J., Carter, C. S., & Anderson, J. R. (2007). Anticipation of conflict monitoring in the anterior cingulate cortex and the prefrontal cortex. Proceedings of National Academy of Science, 104, 10330-10334.

Cassenti, D.N. (2007). ACT-R model of EEG latency data. Proceedings of the Human Factors and Ergonomics Society 51st Annual Meeting (pp. 812-816). Santa Monica, CA: Human Factors and Ergonomics Society.

Ritter, F. E., Kukreja, U., & St. Amant, R. (2007). Including a model of visual processing with a cognitive architecture to model a simple teleoperation task. Journal of Cognitive Engineering and Decision Making, 1(2), 121-147.

St. Amant, R., Horton, T. E., & Ritter, F. E. (2007). Model-based evaluation of expert cell phone menu interaction. ACM Transactions on Computer-Human Interaction, 14(1), Article 1 (May 2007), 24 pages.

Ritter, F. E., Schoelles, M., Klein, L. C., & Kase, S. E. (2007). Modeling the range of performance on the serial subtraction task. In Proceedings of the 8th International Conference on Cognitive Modeling. Lewis, R. L., Polk, T. A., Laird, J. L., (eds.). 299-304. Oxford, UK: Taylor & Francis/Psychology Press.

St. Amant, R., McBride, S. P., Ritter, F. E. (2007). AI support for building cognitive models. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06) (pp. 1663-1666). Menlo Park, CA: AAAI Press.

Qin, Y., Bothell, D., & Anderson, J. R. (2007). ACT-R meets fMRI. In Proceedings of LNAI 4845 (pp.. 205-222). Berlin, Germany: Springer-Verlag.

Shibata, M., Abe, J., Terao, A., & Miyamoto, T. (2007). Neural mechanisms involved in the comprehension of metaphoric and literal sentences: An fMRI study. Brain Research, 1166, 92-102.

Van Maanen, L. (2007). Mediating expert knowledge and visitor interest in art work recommendation. In proceedings of LWA 2007, Halle (Saale), Germany.

Danker, J. M. & Anderson, J. R. (2007). The Roles of Prefrontal and Posterior Parietal Cortex in Algebra Problem Solving: A Case of Using Cognitive Modeling to Inform Neuroimaging Data. NeuroImage. 35, 1365-1377.

Ritter, S., Anderson, J. R., Koedinger, K. R., & Corbett, A. (2007) Cognitive Tutor: Applied research in mathematics education. Psychonomic Bulletin & Review, 14, 249-255.

Das, A., & Stuerzlinger, W. (2007). A Cognitive Simulation Model for Novice Text Entry on Cell Phone Keypads. In Proceedings of the European Conference on Cognitive Ergonomics: ECCE 2007 (pp. 141-147). London, UK.

Anderson, J. R. (2007). Using brain imaging to guide the development of a cognitive architecture. In W. D. Gray (Ed.), Integrated Models of Cognitive Systems (pp. 49-62).New York, NY: Oxford University Press.

Anderson, J. R. (2007). The Algebraic Brain. In Gluck, M. A., Anderson, J. R , & Kosslyn, S. M. (Eds.). Memory and Mind: A Festschrift for Gordon H. Bower. New Jersey: Lawrence Erlbaum Associates.

Kennedy, W.G., & Trafton, J.G. (2007) Using Simulations to Model Shared Mental Models. In Proceedings of the 8th International Conference on Cognitive Modeling Ann Arbor, Michigan, USA.

Serna, A., Pigot, H., & Rialle, V. (2007). Modeling the progression of Alzheimer's disease for cognitive assistance in smart homes. User Modeling and User-Adapted Interaction, 17, 415-438.

Fu, W.-T., & Gray, W. D. (2006). Suboptimal tradeoffs in information seeking. Cognitive Psychology, 52(3), 195-242.

Best, B. J. & Lebiere, C. (2006). Cognitive agents interacting in real and virtual worlds. In R. Sun (ed.), Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press; New York, NY, 186-218.

Ritter, F. E. & Norling, E. (2006) Including Human Variability in a Cognitive Architecture to Improve Team Simulation. In R. Sun (ed.) Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press; New York, NY, 417-427.

West, R. L. , Lebiere, C. & Bothell, D. J. (2006). Cognitive architectures, game playing, and human evolution. In R. Sun (ed.), Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press; New York, NY, 103-123.

Ritter, F. E., Reifers, A. L., Klein, A. C., & Schoelles, M. J. (2006). Lessons from defining theories of stress. In W. Gray (Ed.) Integrated Models of Cognitive Systems. New York, NY: Oxford University Press.

Best, B. J. & Lovett, M. (2006). Inducing a cognitive model from examples provided by an optimal algorithm. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 56-61). Trieste, Italy.

Jones, R. M., Crossman, J. A., Lebiere, C., & Best, B. J. (2006). An abstract language for cognitive modeling. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 160-165). Trieste, Italy.

Kim, J. W., Ritter, F. E., & Koubek, R. J. (2006). ESEGMAN: A substrate for ACT-R architecture and an Emacs LISP application. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 375-376). Trieste, Italy.

Huss, D., Taatgen, N. A., & Anderson, J. R. (2006). Instructional Representation in cognitive modeling. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 367-368). Trieste, Italy.

Cochran, R. E., Lee, F. J., & Chown, E. (2006). Modeling emotion: Arousal's impact on memory In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1133-1138) . Vancouver, British Columbia, Canada.

Stewart, T. C. (2006). Tools and techniques for quantitaive and predictive cognitive science. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 816-821 ) . Vancouver, British Columbia, Canada.

Brunstein, A. (2006). Constructing racing cars: Reducing problem complexity for the fastest car ever seen. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 2452 ) . Vancouver, British Columbia, Canada.

Kao, Y. & Anderson, J. R. (2006). What are they thinking? Decomposing a complex task. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 2523) . Vancouver, British Columbia, Canada.

Najjar, M. & Mayers, A. (2006). Retrieving remembrances via a computational cognitive model of knowledge representation. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1868-1869) . Vancouver, British Columbia, Canada.

Budiu, R., Pirolli, P., & Fleetwood, M. (2006). Navigation of degree of interest trees. In Proceedings of the Advanced Visual Interfaces Conference (AVI’06), Venice, Italy.

Peebles, D. J. & Cox, A. L. (2006). Modelling Interactive Behaviour with a Rational Cognitive Architecture. In P. Zaphiris & S. Kurniawan (Eds.). Human Computer Interaction Research in Web Design and Evaluation. London. Idea Group Inc.

Taatgen, N. A., Huss, D., & Anderson, J. R. (2006). How cognitive models can inform the design of instructions. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 304-309). Trieste, Italy.

Gluck, K. A., Gunzelmann, G., Gratch, J., Hudlicka, E., & Ritter, F. E. (2006, July). Modeling the Impact of Cognitive Moderators on Human Cognition and Performance. Symposium abstract in R.Sun & N Miyake (Eds.), Proceedings of the Twenty-Eighth Annual Meeting of the Cognitive Science Society (p. 2658). Mahwah, NJ: Lawrence Erlbaum Associates.

Jastrzembski, T. S., Gluck, K. A., & Gunzelmann, G. (2006). Knowledge tracing and prediction of future trainee performance. In Proceedings of the 2006 Interservice/Industry Training, Simulation, and Education Conference (pp. 1498-1508). Orlando, FL: National Training Systems Association.

Schoelles, M. J., Neth, H., Myers, C. W., & Gray, W. D. (2006). Steps towards integrated models of cognitive systems: A levels-of-analysis approach to comparing human performance to model predictions in a complex task environment. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 756-761 ) . Vancouver, British Columbia, Canada.

Ritter, F. E., van Rooy, D., St. Amant, R., & Simpson, K. (2006). Providing user models direct access to interfaces: An exploratory study of a simple interface with implications for HRI and HCI. IEEE Transactions on Systems, Man, and Cybernetics: Part A, Systems and Humans, 36(3), 592-601.

Ritter, F. E., Haynes, S. R., Cohen, M., Howes, A., John, B., Best, B. J., Lebiere, C., Jones, R. M., Crossman, J., Lewis, R. L., St. Amant, R., McBride, S. P., Urbas, L., Leuchter, S., & Vera, A. (2006). High-level behavior representation languages revisited. Symposium at Trieste: Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 404-407). Trieste, Italy.

Van Maanen, L., Borst, J. P., Janssen, C. P., & Van Rijn, H. (2006). Memory structures as user models, In proceedings of the 13th Annual ACT-R Workshop. Pittsburgh, PA.

Fu, W.-T., Bothell, D., Douglass, S., Haimson, C., Sohn, M.-H., & Anderson, J. A. (2006), Toward a Real-Time Model-Based Training System. Interacting with Computers, 18(6), 1216-1230.

Gross, J. B., Gunzelmann, G., Gluck, K. A., Van Dongen, H. P. A., & Dinges, D. F. (2006). Computational modeling of the combined effects of circadian rhythm and sleep deprivation. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 297-302 ) . Vancouver, British Columbia, Canada.

Sohn, M.-H., Goode, A., Stenger, V. A, Jung, K.-J., Carter, C. S., & Anderson, J. R. (2005). An information-processing model of three cortical regions: Evidence in episodic memory retrieval, NeuroImage , 21-33.

Pirolli, P. (2005) Rational analyses of information foraging on the web. Cognitive Science, 29, 343-373.

Stocco, A., & Fum, D., (2005) Somatic markers and memory for outcomes: Computational and experimental evidence. In Proceedings of the 14th Annual Conference of the European Society for Cognitive Psychology (ESCoP).

Stocco, A., Fum, D., & Zalla, T. (2005). Revising the role of somatic markers in the Gambling Task: A computational account for neuropsychological impairments. In B. Bara, L. Barsalou & M. Bucciarelli (Eds.), Proceedings of the 27th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates.

Mathan, S. A. & Koedinger, K. R. (2005) Fostering the Intelligent Novice: Learning from Errors with Metacognitive Tutoring. Educational Psychologist 40(4), 257-265.

Anderson, J. R., Albert, M. V., & Fincham, J.M. (2005) Tracing Problem Solving in Real Time: fMRI Analysis of the Subject-Paced Tower of Hanoi. Journal of Cognitive Neuroscience, 17 1261-1274.

Gluck, K. A., Ball, J. T., Gunzelmann, G., Krusmark, M. A., Lyon, D. R., & Cooke, N. J. (2005). A prospective look at a synthetic teammate for UAV applications. In Proceedings of the American Institute of Aeronautics and Astronautics Infotech@Aerospace Conference. Reston, VA: American Institute of Aeronautics and Astronautics.

Jung, K.-J., Prasad, p., Qin, Y., & Anderson, J. R. (2005). Extraction of overt verbal response from acoustic noise from the scanner in fMRI by use of segmented active noise cancellation. Magnetic Resonance Imaging, 53, 739-744.

Anderson, J. R. (2005). Cognitive Psychology and Its Implications: Sixth Edition. New York: Worth Publishing.

St. Amant, R., Freed, A. R., & Ritter, F. E. (2005). Specifying ACT-R models of user interaction with a GOMS language. Cognitive Systems Research, 6, 71-88.

St. Amant, R., Riedl, M. O., Ritter, F. E., & Reifers, A. (2005). Image processing in cognitive models with SegMan. In Proceedings of HCI International, 2005. (Invited.) Volume 4 - Theories Models and Processes in HCI. Paper # 1869.

John, B. E. & Salvucci, D. D. (2005) Multi-Purpose Prototypes for Assessing User Interfaces in Pervasive Computing Systems. IEEE Pervasive Computing 4(4), 27-34.

Lebiere, C. (2005). Constrained functionality: Application of the ACT-R cognitive architecture to the AMBR modeling comparison. In K. A. Gluck and R. Pew, editors, Modeling Human Behavior With Integrated Cognitive Architectures, Mahwah, NJ: Erlbaum.

Gunzelmann, G., Gluck, K. A., Van Dongen, H. P. A., O'Conner, R. M., & Dinges, D. F. (2005). A neurobehaviorally inspired ACT-R model of sleep deprivation: Decreased performance in psychomotor vigilance. In B. G. Bara, L. Barsalou, and M. Bucciarelli (Eds.), Proceedings of the Twenty-Seventh Annual Meeting of the Cognitive Science Society, (pp. 857-862). Mahwah, NJ: Lawrence Erlbaum Associates.

Roll, I., Baker, R. S., Aleven, V., & Koedinger, K. (2004). A Metacognitive ACT-R Model of Students' Learning Strategies in Intelligent Tutoring Systems. In Proceedings the Seventh International Conference of Intelligent Tutoring Systems (pp. 854-856) Lecture Notes in Computer Science 3220. Berlin: Springer Verlag.

Brumby, D. P. & Howes, A. (2004). Good enough but I'll just check: Web-paged search as attentional refocusing. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 46-51). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

John, B. E., Salvucci, D. D., Centgraf, P., Prevas, K. (2004). Integrating models and tools in the context of driving and in-vehicle devices. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 130-135). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Fum, D. & Stocco, A. (2004). Memory, emotion, & rationality: An ACT-R interpretation for gambling task results. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 106-111). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Roll, I., Baker, R. S., Aleven, V., & Koedinger, K. (2004). What goals do students have when choosing the actions they perform? In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 380-381). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Kim, S.-Y., Lodge, M., & Taber, C. (2004). A computational model of voter- The dynamics of political candidate evaluation. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 362-363). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

West, R. L. & Emond, B. (2004). The environment as theory: An example using the ACT-R/SOS environment. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 398-399). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Brumby, D. P. (2004) A model of single-page web search: The effect of interdependence on link assessment. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 402-403). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Anderson, J. R., Douglass, S. & Qin, Y. (2004). How should a theory of learning and cognition inform instruction?. In A. Healy (Ed.) Experimental cognitive psychology and it’s applications. American Psychological Association; Washinton, D. C.

Tor, K., Ritter, F. E., Haynes, S. R., & Cohen, M. A. (2004). CaDaDis: A tool for displaying the behavior of cognitive models and agents. In Proceedings of the 13th Conference on Behavior Representaion in Modeling and Simulation. 04-BRIMS-032. 192-200. Orlando, FL: University of Central Florida.

Howes, A., Vera, A., Lewis, R. L., & McCurdy, M. (2004). Cognitive constraint modeling: A formal approach to supproting reasoning about behavior. In proceedings of the 26th Annual Conference of the Cognitive Science Society (pp.595-600) . August 4-7, Chicago, USA

Matessa, M. (2004) An ACT-R modeling framework for interleving templates of human behavior. In proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 903-908) . August 4-7, Chicago, USA

Rehling, J., Lovett, M., Lebiere, C., Reder, L. M., & Demiral, B. (2004) Modeling complex tasks: An individual difference approach. In proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 1137-1142) . August 4-7, Chicago, USA

Sohn, M.-H., Goode, A., Koedinger, K. R., Stenger, V. A, Fissell, K., Carter, C. S., & Anderson, J. R. (2004). Behavioral equivalence but not neural equivalence: Neural evidence of alternative strategies in mathematical thinking. Nature Neuroscience, 7 (11), 1193-1194.

Haimson, C., Bothell, D., Douglass, S. A., & Anderson, J. R. (2004) Partitioning visual displays aids task-directed search. Human Factors: The Journal of Human Factors and Ergonomics Society, 3, 551-566 (16).

Koedinger, K.R. & Mathan, S. (2004) Distinguishing qualitatively different kinds of learning using log files and learning curves. ITS 2004 Log Analysis Workshop Maceio, Brazil, 39-46.

Anderson, J. R., Qin, Y., Stenger, V. A., & Carter, C. S. (2004). The relationship of three cortical regions to an information-processing model. Journal of Cognitive Neuroscience, 16 (4), 637-653.

Sohn, M.-H., Goode, A., Stenger, V. A, Carter, C. S., & Anderson, J. R. (2003). Competition and representation during memory retrieval: Roles of the prefrontal cortex and the posterior parietal cortex, Proceedings of National Academy of Sciences, 100, 7412-7417.

Qin, Y., Carter, C. S., Silk, E., Stenger, V. A., Fissell, K., Goode, A. & Anderson, J.R. (2004). The change of the brain activation patterns as children learn algebra equation solving. Proceedings of National Academy of Sciences,101(15), 5686-5691.

Pirolli, P. L. (2004). The Use of Proximal Information Scent to Forage for Distal Content on the World Wide Web. In Alex Kirlik (Ed.) Working with Technology in Mind: Brunswikian Resources for Cognitive Science and Engineering. New York, NY: Oxford University Press.

Gunzelmann, G., & Gluck, K. A. (2004). Knowledge tracing for complex training applications: Beyond Bayesian mastery estimates. In Proceedings of the Thirteenth Conference on Behavior Representation in Modeling and Simulation (pp. 383-384). Orlando, FL: Simulation Interoperability Standards Organization.

Veksler, V. D. & Gray, W. D. (2004). State definition in the Tetris task: designing a hybrid model of cognition. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 394-395). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

St. Amant, R., Horton, T. E., & Ritter F. E. (2004). Model-based evaluation of cell phone menu interaction. In Proceedings of the CHI'04 Conference on Human Factors in Computer Systems 343-350. New York, NY: ACM.

Ritter, F. E., Reifers, A., Klein, L. C., Quigley, K., & Schoelles, M. (2004). Using cognitive modeling to study behavior moderations: Pre-task appraisal and anxiety. In Proceedings of the Human factors and Ergonomics Society (pp. 2121-2125). Santa Monica, CA: Human Factor and Ergonomics Society.

St. Amant, R. & Ritter, F. E. (2004). Automated GOMS-to-ACT-R model generation. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 26-31). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Tor, K., Haynes, S. R., Ritter, F. E., & Cohen, M. A. (2004). Categorical data displays generated from three cognitive architectures illustrate their behavior. In Proceedings of the International Conference on Cognitive Modeling (pp. 302-307). Mahwah, NJ: Lawrence Erlbaum.

Tor, K. & Ritter, F. E. (2004). Using a genetic algorithm to optimize the fit of cognitive models. In Proceedings of the Sixth International Conference on Cognitive Modeling. Mahwah, NJ: Lawrence Erlbaum.

Ritter, F. E. (2004). Choosing and getting started with a cognitive architecture to test and use human-machine interfaces. MMI-Interaktiv-Journal's special issue on Modeling and Simulation in Human-Machine Systems, 7. 17-37.

John, B. E., Prevas, K., Salvucci, D. D., Koedinger, K. (2004) Predictive human performance modeling made easy. In Proceedings of CHI 2004 (Vienna, Austria, April 2004), ACM New York. 455-462.

Terao, A., Koedinger, K. R., Sohn, M-H., Qin, Y., Anderson, J. R., & Carter, C. S. (2004). An fMRI study of the interplay of symbolic and visuo-spatial systems in mathematical reasoning.In Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 1327-1332).

Fu, W.-T. & Gray, W. D. (2004). Resolving the paradox of the active user: Stable suboptimal performance in interactive tasks. Cognitive Science, 28(6), 901-935.

Van Rijn, H., van Someren, M., & van der Maas, H.L.J. (2003). Modeling developmental transitions on the balance scale task. Cognitive Science, 27(2), 227-257.

Baker, R.S., Corbett, A.T., Koedinger, K.R. (2003) Statistical Techniques For Comparing ACT-R Models of Cognitive Performance. In Proceedings of the 10th Annual ACT-R Workshop, 129-134.

Kushleyeva, Y & Salvucci, D. D. (2003) Human Multitasking: Towards an ACT-R Task-Independent General Executive. In Proceedings of the 25th Annual Meeting of the Cognitive Science Society. pg 1369.

Rehling, J., Demiral, B., Lebiere, C., Lovett, M., & Reder, L. M. (2003). Modeling individual difference factors in a complex task environment. In F. Detje, D. Doerner, & H. Schaub (Eds.), In Proceedings of the Fifth International Conference on Cognitive Modeling (pp. 287-288). Bamberg, Germany: Universitats-Verlag Bamberg.

Lee, F. J. & Gamard, S. J. (2003) Hide and Seek: Using Computational Cognitive Models to Develop and Test Autonomous Cognitive Agents for Complex and Dynamic Tasks. In Proceedings of the 25th Annual Meeting of the Cognitive Science Society. pg 1372.

Salvucci, D.D., & Lee, F. J. (2003). Simple cognitive modeling in a complex cognitive architecture. In Human Factors in Computing Systems: CHI 2003 Conference Proceedings (pp. 265-272). New York: ACM Press.

Pirolli, P. L. & Fu, W-T. (2003)SNIF-ACT: A Model of Information Foraging on the World Wide Web. Ninth International Conference on User Modeling, Johnstown, PA .

Shah, K., Rajyaguru, S., St. Amant, R., & Ritter, F. E. (2003). Connecting a cognitive model to dynamic gaming environments: Architectural and image processing issues. In F. Detje, D. Doerner, & H. Schaub (Eds.), Proceedings of the Fifth International Conference on Cognitive Modeling. 189-194. Bamberg, Germany: Universitats-Verlag Bamberg.

Qin, Y., Sohn, M-H, Anderson, J. R., Stenger, V. A., Fissell, K., Goode, A. Carter, C. S. (2003). Predicting the practice effects on the blood oxygenation level-dependent (BOLD) function of fMRI in a symbolic manipulation task. Proceedings of the National Academy of Sciences of the United States of America. 100(8): 4951-4956.

West, R.L, Emond B. (2002). SOS: A simple operating system for modeling HCI with ACT-R. Seventh Annual ACT-R Workshop. Pittsburgh, PA : Department of Psychology, Carnegie Mellon University, 2 p.

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.

Lebiere, C., & Shang, J. (2002). A cognitive architecture-based theory of meliorative behavior. In Proceedings of the 8th Behavioral Decision Research in Management Conference (BDRM). Chicago, IL.

Lebiere, C., Biefeld, E., Archer, R., Archer, S., Allender, L., & Kelley, T. (2002). IMPRINT/ACT-R: Integration of a task network modeling architecture with a cognitive architecture and its application to human error modeling. In Proceedings of the Advanced Technologies Simulation Conference. San Diego, CA.

Lebiere, C. (2002). Modeling group decision making in the ACT-R cognitive architecture. In Proceedings of the 2002 Computational Social and Organizational Science (CASOS). June 21-23, Pittsburgh, PA.

Craig, K., Doyal, J., Brett, B., Lebiere, C., Biefeld, E., & Martin, E. (2002). Development of a hybrid model of tactical fighter pilot behavior using IMPRINT task network model and ACT-R. In Proceedings of the Eleventh Conference on Computer Generated Forces and Behavior Representation. Orlando, FL.

Best, B., Lebiere, C., & Scarpinatto, C. (2002). A model of synthetic opponents in MOUT training simulations using the ACT-R cognitive architecture. In Proceedings of the Eleventh Conference on Computer Generated Forces and Behavior Representation. Orlando, FL.

Triona, L. M., Masnick, A. M., & Morris, B. J. (2002). What does it take to pass the false belief task? An ACT-R Model. In Proceedings of the 24th Annual Meeting of the Cognitive Science Society, Fairfax, VA: August, 2002.

Ritter, F. E., Avraamides, M., & Councill, I. G. (2002). An approach for accurately modeling the effects of behavior moderators. In Proceedings of the 11th Computer Generated Forces Conference. 29-40, 02-CGF-002. Orlando, FL: U. of Central Florida.

Anderson, J. R. (2002). Spanning seven orders of magnitude: A challenge for cognitive modeling. Cognitive Science, 26, 85-112

Anderson, J. R., Qin, Y., Sohn, M-H., Stenger, V. A. & Carter, C. S. (2003) An information-processing model of the BOLD response in symbol manipulation tasks. Psychonomic Bulletin & Review. 10, 241-261.

Fincham, J. M., Carter, C. S., van Veen, V., Stenger, V. A., & Anderson, J. R. (2002). Neural mechanisms of planning: A computational analysis using event-related fMRI. In Proceedings of the National Academy of Sciences. 99 (5), 3346-3351, 2002.

Schooler, L. J. (2001). Rational theories of cognition in psychology. In W. Kintch, N. Smelser, P. Baltes, (Eds.), International Encyclopedia of the Social and Behavioral Sciences. Oxford, UK: Pergamon.

Daily, L. Z., Lovett, M. C., & Reder, L. M. (2001). Modeling individual differences in working memory performance: A source activation account in ACT-R. Cognitive Science 25, 315-353.

Wagenmakers, E. M., Zeelenberg, R., Schooler, L. J., & Raaijmakers, J. G. W. (2001). A criterion-shift model for enhanced discriminability in perceptual identification: A note on the counter model. Psychonomic Bulletin, & Review, 7, 718-726.

Taatgen, N. A. (2001). A model of individual differences in learning Air Traffic Control. In Proceedings of the Fourth International Conference on Cognitive Modeling, pp. 211-216. Mahwah, NJ: Lawrence Erlbaum Associates.

Fum, D. & Del Missier, F. (2001). Modeling counter offer behavior in dyadic distributive negotiation. In Proceedings of the Fourth International Conference on Cognitive Modeling, pp. 79-84. Mahwah, NJ: Lawrence Erlbaum Associates.

Belavkin, R. V. (2001). The Role of Emotion in Problem Solving. In Proceedings of the AISB'01 Symposium on Emotion, Cognition and Affective Computing (pp. 49--57). Heslington, York, England.

Lebiere, C. (2001). A theory-based model of cognitive workload and its applications. In Proceedings of the 2001 Interservice/Industry Training, Simulation and Education Conference (I/ITSEC). Arlington, VA: NDIA.

Matessa, M. (2001). Simulating adaptive communication. Ph.D. Thesis, Carnegie Mellon University, Pittsburgh, PA.

Emond, B. & Ferres, L. (2001) Modeling the False-Belief Task: An ACT-R Implementation of Wimmer & Perner (1983). Second Bisontine Conference for Conceptual and Linguistic Development in the Child Aged from 1 to 6 Years. Besançon (France), March 21-23 2001.

Anderson, J. R. & Gluck, K. (2001). What role do cognitive architectures play in intelligent tutoring systems? In D. Klahr & S. M. Carver (Eds.) Cognition & Instruction: Twenty-five years of progress, 227-262. Erlbaum.

Schooler, L. J., Shiffrin, R. M., & Raaijmakers, J. G. W. (2001). Theoretical Note: A Bayesian model for implicit effects in perceptual identification. Psychological Review, 108, pp. 257-272.

Corbett, A. T. & Anderson, J. R. (2001). Locus of feedback control in computer-based tutoring: Impact on learning rate, achievement and attitudes. In Proceedings of ACM CHI'2001 Conference on Human Factors in Computing Systems, 245-252.

Ritter, F. E., & Young, R. M. (2001). Embodied models as simulated users: Introduction to this special issue on using cognitive models to improve interface design. International Journal of Human-Computer Studies, 55, 1-14.

Matessa, M. (2001). Interactive models of collaborative communication. In Proceedings of the Twenty-third Annual Conference of the Cognitive Science Society (pp. 634-638). Hillsdale, NJ: Lawrence Erlbaum Associates.

Jones, G., Ritter, F. E., & Wood, D. J. (2000). Using a cognitive architecture to examine what develops. Psychological Science, 11(2), 1-8.

Lovett, M. C., Daily, L. Z., & Reder, L. M. (2000). A source activation theory of working memory: Cross-task prediction of performance in ACT-R. Cognitive Systems Research, 1, 99-118.

Anderson, J. R. & Schunn, C. D. (2000). Implications of the ACT-R learning theory: No magic bullets. In R. Glaser, (Ed.), Advances in instructional psychology: Educational design and cognitive science (Volume 5), pp. 1-34. Mahwah, NJ: Lawrence Erlbaum Associates.

Anderson, J.R., Reder, L.M., & Simon, H.A. (2000, Summer). Applications and Misapplications of Cognitive Psychology to Mathematics Education. Texas Educational Review

Matessa, M., & Anderson, J. R. (2000). Modelling Focused Learning in Role Assignment. Language and Cognitive Processes, 15 (3), 263-292.

Gluck, K. A., Lovett, M. C., Anderson, J. R., & Shute, V. J. (unpublished). The Curriculum and the Interface: A Componential Analysis of the Learning Curve.

Anderson, J. R. (2000). Cognitive Psychology and Its Implications: Fifth Edition. New York: Worth Publishing.

Anderson, J. R. (2000). Learning and Memory, Second Edition. New York: Wiley.

Anderson, J. R., Greeno, J. G., Reder, L. M., & Simon, H. A. (2000). Perspectives on learning, thinking, and activity. Educational Researcher, 29, 11-13.

van Rijn, H., Someren, M., & van der Maas, H. (2000). Modeling developmental transitions in ACT-R. Simulating balance scale behavior by symbolic and subsymbolic learning. In Proceedings of the Third International Conference on Cognitive Modeling, pp. 226-233. Groningen: Universal Press.

Sohn, M.-H., Ursu, S., Anderson, J. R., Stenger, V. A., & Carter, C. S. (2000). The role of prefrontal cortex and posterior parietal cortex in task-switching. In Proceedings of National Academy of Science, 97 (24), 13448-13453.

Jones, G., & Ritter, F. E. (2000). Over-estimating cognition time: The benefits of using a task simulation. In Simulating Human Agents, American Association for Artificial Intelligence Fall 2000 Symposium Series (pp. 67-74). Menlo Park, CA: AAAI Press.

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

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.

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.

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.

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.

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.

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.

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.

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

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).

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

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

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.

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.

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.

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.

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. (1996). Situated learning and education. Educational Researcher, 25, 5-11.

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.

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.

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

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

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

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.

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

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.

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.

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., 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.

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. (1992). Student modeling and mastery learning in a computer-based programming tutor. 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 .

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

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

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.

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.

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.

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). Cognitive Psychology and its Implications: Third Edition. New York: Freeman.

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

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

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

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

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

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.

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

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

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., & 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.

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

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

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

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.

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

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

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

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

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

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

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

Fu, W.-T., Pirolli, P. (in press), SNIF-ACT: A Model of Information-Seeking Behavior in the World Wide Web. Human-Computer Interaction.

Copyright © 2002-2013 ACT-R Research Group


Department of Psychology, Carnegie Mellon University