ABSTRACT
This book has reported the results of our efforts to make ACT–R a theory capable of modeling a wide range of phenomena. The key step in that development has been reducing the size of ACT–R’s knowledge units to what have been advertised as the atomic components of thought As a result of this commitment to a consistent, atomic grain size in knowledge representation, modeling in ACT–R has become much more principled and there has been a substantial convergence on the values for the subsymbolic parameters that control the system. This book described some of the in-house applications of ACT–R as demonstrations of the productivity of this approach. However, these application are but a few of the many that researchers have developed. As a better representation of the range of applications of ACT–R, Table 12.1 lists the research papers presented at the 4th Annual ACT–R Workshop in August 1997. The range of applications is truly gratifying in that it indicates that ACT–R is becoming a useful tool for modeling many aspects of human cognition. This breadth of application is a sign that the ACT–R theory is capturing significant generalizations about the nature of human cognition. Papers Presented at the 1997 ACT–R Summer Workshop
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Saturday, August 2 |
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Session 1 |
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Bruno Emond |
Models of natural language comprehension and parsing |
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Eric Scott |
Implementing a schema theory in ACT–R |
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Mike Matessa |
Focused learning in linguistic role assignment |
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Session 2 |
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Kevin Gluck |
Learning to learn from a computer-based tutor: An ACT–R model as proof-of-concept |
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Chris Schunn |
Psychologist in a box: An ACT–R model that designs and interprets experiments |
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Brian Ehret |
ACT–R models of submariner situation assessment |
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Wayne Gray & Erik Altmann |
Dynamic microstrategies as an explanation of cognitive workload |
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Sunday, August 3 |
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Session 1 |
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Tony Simon |
Computational evidence for the nonnumerical basis of number competence |
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Todd Johnson |
Computation and retrieval in alphabet arithmetic |
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Christian Lebiere |
Lessons from cognitive arithmetic |
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Session 2 |
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Marsha Lovett, Lynne Reder, & Christian Lebiere |
Modeling working memory effects at the individual level |
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Dieter Wailach |
Modeling complex problem solving |
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John Anderson & Jonathan Betz |
Modeling categorization in ACT–R |
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Niels Taatgen |
Explicit learning in ACT–R |
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Monday, August 4 |
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Session 1 |
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Joyce Tang Boyland |
Modeling syntactic priming in ACT–R |
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Todd Johnson |
Multistrategy learning and transfer in tic-tac-toe |
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Ken Koedinger & Ben MacLaren |
Modeling strategy learning in early algebra |
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Session 2 |
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Frank Lee |
Eye tracking in the air traffic controller task |
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Dario Salvucci |
Relating ACT–R models and eye movement protocols |
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Tony Simon |
Modeling a functional limit to the subitizing phenomenon |
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Mike Byrne |
ACT–R and PRP |
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Tuesday, August 5 |
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Session 1 |
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Raluca Vasilescu |
An ACT–R model for learning anaphoric metaphors |
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Peter Brusilovsky |
ACT–R on the Web |
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John Anderson, Dan Bothell, Scott Douglass, & Christian Lebiere |
ACT–R models of the navigation task |
