Constrained Functionality: Application of the ACT-R Cognitive Architecture to the AMBR Modeling Comparison

Symbolic Level ACT-R is a production system theory that models the steps of cognition by a sequence of production rules that fire to coordinate retrieval of information from the environment and from memory. It is a cognitive architecture that can be used to model a wide range of human cognition. It has been used to model tasks from memory retrieval (Anderson, Bothell, Lebiere & Matessa, 1998) to visual search (Anderson, Matessa & Lebiere, 1997). The range of models developed, from those purely concerned with internal cognition to those focused on perception and action, makes ACT-R a plausible candidate to model a task like the air traffic control simulation described previously because the task includes all of these various components. In all domains, ACT-R is distinguished by the detail and fidelity with which it models human cognition. It makes claims about what

[1]  J. G. Hollands,et al.  Engineering Psychology and Human Performance , 1984 .

[2]  Geoffrey E. Hinton,et al.  A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..

[3]  Richard Reviewer-Granger Unified Theories of Cognition , 1991, Journal of Cognitive Neuroscience.

[4]  Christian Lebiere,et al.  Sequence Learning in the ACT-R Cognitive Architecture: Empirical Analysis of a Hybrid Model , 2001, Sequence Learning.

[5]  Albert T. Corbett,et al.  Statistical Techniques For Comparing ACT-R Models of Cognitive Performance , 2003 .

[6]  John R. Anderson,et al.  Why do children learn to say “Broke”? A model of learning the past tense without feedback , 2002, Cognition.

[7]  John R. Anderson,et al.  Student modeling in the ACT Programming Tutor. , 1995 .

[8]  Frank J. Lee,et al.  Does Learning a Complex Task Have to Be Complex?: A Study in Learning Decomposition , 2001, Cognitive Psychology.

[9]  Frank E. Ritter,et al.  Using Cognitive Modeling to Study Behavior Moderators: Pre-Task Appraisal and Anxiety , 2004 .

[10]  Allen Newell,et al.  The psychology of human-computer interaction , 1983 .

[11]  D. Rubin,et al.  One Hundred Years of Forgetting : A Quantitative Description of Retention , 1996 .

[12]  Christian Lebiere,et al.  The dynamics of cognition: An ACT-R model of cognitive arithmetic , 1999, Kognitionswissenschaft.

[13]  John R. Anderson The Adaptive Character of Thought , 1990 .

[14]  C. Lebiere,et al.  The Atomic Components of Thought , 1998 .

[15]  G. Logan Toward an instance theory of automatization. , 1988 .

[16]  Christian Lebiere,et al.  Implicit and explicit learning in ACT-R , 1998 .

[17]  John R. Anderson,et al.  Serial modules in parallel: the psychological refractory period and perfect time-sharing. , 2001, Psychological review.

[18]  A. Miyake,et al.  Models of Working Memory: Mechanisms of Active Maintenance and Executive Control , 1999 .

[19]  John R. Anderson,et al.  Reflections of the Environment in Memory Form of the Memory Functions , 2022 .

[20]  H Pashler,et al.  How persuasive is a good fit? A comment on theory testing. , 2000, Psychological review.

[21]  John R. Anderson,et al.  A hybrid model of categorization , 2001, Psychonomic bulletin & review.

[22]  C. Lebiere,et al.  An integrated theory of list memory. , 1998 .

[23]  C. Lebiere,et al.  Models of Working Memory: Modeling Working Memory in a Unified Architecture: An ACT-R Perspective , 1999 .

[24]  Christian Lebiere,et al.  Simple games as dynamic, coupled systems: randomness and other emergent properties , 2001, Cognitive Systems Research.

[25]  John R. Anderson,et al.  ACT-R: A Theory of Higher Level Cognition and Its Relation to Visual Attention , 1997, Hum. Comput. Interact..

[26]  Scott Sanner,et al.  Achieving Efficient and Cognitively Plausible Learning in Backgammon , 2000, ICML.