ACT-R

Publications about Choice and Strategy Selection

Altmann, E. M. & Burns, B . D. (2004). Streak biases in decision making: Data and a memory model. In Proceedings of the sixth International Conference on Cognitive Modeling (pp.34-39). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh. [PDF] [info]

Altmann, E. M. & Burns, B. D. (2005). Streak biases in decision making: data and a memory model. Cognitive Systems Research, 6, 5-16. [PDF] [info]

Beaman, C. P., McCloy, R. A., & Smith, P. T. (2006). When does ignorance make use smart? Additional factors guiding heuristic inference. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 54-58 ) . Vancouver, British Columbia, Canada. [PDF] [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 [PDF] [info]

Belavkin, R. V., & Ritter, F. E. (2003). The use of entropy for analysis and control of cognitive models. In F. Detje, D. Doerner, & H. Schaub (Eds.), Proceedings of the Fifth International Conference on Cognitive Modeling. 21-26. Bamberg, Germany: Universitats-Verlag Bamberg. [PDF] [info]

Belavkin, R. V. & Ritter, F. E. (2004). OPTIMIST: A new conflict resolution alogorithm for ACT-R. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 40-45). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh. [PDF] [info]

Belvakin, R. V. (2006). Towards a theory of decision-making without paradoxes. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 38-43). Trieste, Italy. [PDF] [info]

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

Del Missier, F. & Fum, D. (2002) Declarative and procedural strategies in problem solving: Evidence from the toads and frogs puzzle. In W. D. Gray & C. D. Schunn (Eds.), Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society, Mahwah, NJ: Lawrence Erlbaum Associates, 262-267. [PDF] [info]

Fu, W-T. (2001). The influence of experienced effort on learning and choice solution paths in a simple navigation task. In Proceedings of the Fourth International Conference on Cognitive Modeling, pp. 279-280. Mahwah, NJ: Lawrence Erlbaum Associates. [PDF] [info]

Fu, W-T. & Anderson, J. R. (2004). Extending the Computational Abilities of the Procedural Learning Mechanism in ACT-R. In proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 416-421). August 4-7, Chicago, USA [PDF] [info]

Fu, W-T. & Anderson, J. R. (2006). From recurrent choice to skill learning: A reinforcement-learning model. Journal of Experimental Psychology: General, 135(2), 184-206. [PDF] [info]

Fu, W-T., & Gray, W. D. (2001). Modeling cognitive versus perceptual-motor tradeoffs using ACT-R/PM. In Proceedings of the Fourth International Conference on Cognitive Modeling, pp. 247-248. Mahwah, NJ: Lawrence Erlbaum Associates. [PDF] [info]

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

Gray, W. D., Schoelles, M. J., & Sims, C. R. (2004). Learning to choose the most effective strategy: Explorations in expected value. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 112-117). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh. [PDF] [info]

Gray, W. D., Schoelles, M. J., & Sims, C. R. (2005). Adapting to the task environment: Explorations in expected value. Cognitive Systems Research, 6, 27-40. [PDF] [info]

Gray, W. D., Sims, C. R., Fu, W.-T., & Schoelles, M. J. (2006). The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior. Psychological Review, 113(3), 461-482. [PDF] [info]

Gugerty, L. (in press, publication expected May 2007). Cognitive components of troubleshooting strategies. Thinking and Reasoning. [PDF] [info]

Gunzelmann, G. F. (2006). Understanding similarities in performance on different orientation tasks: Strategy adaptation. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 124-129). Trieste, Italy. [PDF] [info]

Janssen, C.P., Gray, W.D., & Schoelles, M.J. (2008). How a Modeler's Conception of Rewards Influences a Model's Behavior: Investigating ACT-R 6's Utility Learning Mechanism. In Proceedings of the 15th Annual ACT-R Workshop (p. 42), Pittsburgh, PA. [PDF] [info]

Lebiere, C., Gray, R., Salvucci, D. & West R. (2003) Choice and Learning under Uncertainty: A Case Study in Baseball Batting. In Proceedings of the 25th Annual Meeting of the Cognitive Science Society. pg 704-709. [PDF] [info]

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

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

Mckenzie-Kerr, A. & Macken, W. J. (2006). Metamemory in strategy selection: Evidence for a dissocaition in familiarity-based judgments between In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1806-1810) . Vancouver, British Columbia, Canada. [PDF] [info]

Nellen, S. (2003). The use of the "Take-the-Best" heuristic under different conditions, modeled with ACT-R. In: F. Detje, D Doerner and H. Schaub (eds.), Proceedings of the fifth international conference on cognitive modeling (pp. 171-176). Bamberg: Universitaetsverlag Bamberg [PDF] [info]

Nellen, S. & Lovett, M. C. (2004). Towards a theory of balancing exploration and exploitation in probabilistic environments. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 214-219). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh. [PDF] [info]

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. [info]

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. [PDF] [info]

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

Walsh, M. M. & Anderson, J. R. (2009) The strategic nature of changing your mind. Cognitive Psychology, 58, 416-440. [PDF] [info]

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