Publications about Architecture

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

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

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

Anderson, J. R. (2007) How Can the Human Mind Occur in the Physical Universe? New York: Oxford University Press. [HTML][Pyramid model][Linear Equations][Friedman model] [info]

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

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. [] [info]

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. [Document] [][Model] [info]

Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y . (2004). An integrated theory of the mind. Psychological Review 111, (4). 1036-1060. [] [info]

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. [] [info]

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. [] [info]

Anderson, J. R. & Lebiere, C. (1998). The atomic components of thought. Mahwah, NJ: Erlbaum. [Chapter abstracts, model source code, and web-based simulations] [info]

Anderson, J. R., Qin, Y., Jung, K-W., & Carter, C. S. (2007). Information-Processing Modules and their Relative Modality Specificity, Cognitive Psychology, 54(3), 185-217 [] [HTML] [model information] [info]

Belavkin, R. V. (2003). Conflict Resolution by Random Estimated Costs. In D. Al-Dabass (Ed.), Proceedings of 17th European Simulation Multiconference (pp. 105--110). Nottingham, England. ISBN 3-936150-25-7 [] [info]

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. [] [info]

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. [] [info]

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) [] [info]

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. [] [info]

Gunzelmann, G. & Lyon, D. R (2007). Cognitive architectures: Valid control mechanisms for spatial information processing. In H. Schultheis, T. Barkowsky, B. Kuipers, and B. Hommel (Eds.), Technical Report #SS07-01: AAAI Spring Symposium Series: Control Mechanisms for Spatial Knowledge Processing in Cognitive/Intelligent Systems (pp. 23-28). Menlo Park, CA: AAAI Press. [] [info]

Gunzelmann, G. & Lyon, D. R. (2007). Mechanisms of human spatial competence. In T. Barkowsky, M. Knauff, G. Ligozat, & D. Montello (Eds.), Spatial Cognition V: Reasoning, Action, Interaction. Lecture Notes in Artificial Intelligence #4387 (pp. 288-307). Berlin, Germany: Springer-Verlag. [] [info]

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) [] [info]

Kennedy, W. G. (2011). Notes on teaching ACT-R modeling. Retrieved from http://act-r.psy.cmu.edu/papers/1006/notesfortutorial.pdf [] [Document] [info]

Kennedy, W.G., & Trafton, J.G. (2006) Long-term Learning in Soar and ACT-R. In Proceedings of the Seventh International Conference on Cognitive Modeling(pp. 166-171). Trieste, Italy. [Document] [Document] [] [info]

Kennedy, W. G., & Trafton, J.G. (2007) Long-term symbolic learning. Cognitive Systems Research. doi:10.1016/j.cogsys.2007.06.005 [] [HTML] [info]

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. [] [info]

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

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

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. [] [info]

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

Schoppek, W. (2003). Emerging structure in ACT-R: Explorations in competitive chunking In F. Detje, D. Doerner, & H. Schaub (Eds.), In Proceedings of the Fifth International Conference on Cognitive Modeling (pp. 297-298). Bamberg, Germany: Universitats-Verlag Bamberg. [] [info]

Stewart, T. C. & West, R. L. (2006). Deconstructing ACT-R. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 298-303). Trieste, Italy. [] [info]

Stocco, A., Lebiere, C., & Anderson, J. R. (2008). Procedural Learning and Sequential Control of Behavior in a Neural Network Model of the Basal Ganglia. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society, San Francisco, CA, pp. 210-211. [] [info]

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. [] [info]

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. [][Model] [info]

Taatgen, N.A. (2003). Learning rules and productions. In: L. Nadel (Ed.), Encyclopedia of Cognitive Science, vol. 2 (pp. 822-830). London: MacMillan. [HTML] [info]

Taatgen, N.A. & Anderson, J.R. (2008). ACT-R. In R. Sun (ed.), Constraints in Cognitive Architectures. Cambridge University Press, pp 170-185. [] [info]

Taatgen, N.A., Lebiere, C. & Anderson, J.R. (2006). Modeling Paradigms in ACT-R. In R. Sun (ed.), Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press; 29-52. [] [info]

Taatgen, N.A. (winter 2004). Production compilation: a versatile cognitive mechanism. AISB Quarterly p. 7. [HTML] [info]

Tamborello, F. P., II, & Byrne, M. D. (2007). Fast Learning in a Simple Probabilistic Visual Environment: A Comparison of ACT-R’s Old PG-C and New Reinforcement Learning Algorithms. In Proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, Michigan, USA. [] [info]

Young, R. M. (2004). The data learning problem arises also in cognitive architectures other than Soar. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 331-336). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh. [] [info]