A Rule-Based Implementation of ACT-R Using Constraint Handling Rules

Computational Cognitive Modeling is a research field at the interface of computer science and the cognitive sciences. It enables researchers to build detailed cognitive models upon a cognitive architecture which provides some general assumptions about human cognition to simulate human behaviour. By conducting the same experiments with humans and an executable computational cognitive model, the plausibility of a model can be verified. ACT-R is a cognitive architecture which is widely used in the field of computational cognitive modeling. It is a production-rule system whose models are expressed by a set of declarative knowledge elements – the data – and a set of rules. The rules match the data and, if applied, have effects on the data. Constraint Handling Rules (CHR) is a high-level rule-based formalism and programming language which offers a lot of analysis tools for its programs. This work first presents some fundamental aspects of ACT-R and then introduces a translation of ACT-R models to CHR programs. The implementation of ACT-R using Constraint Handling Rules shows that cognitive models can be expressed very elegantly in CHR. Since CHR provides a lot of analysis tools and its rules have a defined declarative semantics, this approach may support the verification of cognitive models. Additionally, the translation of the models is automated by a compiler, so it is not compulsory for modelers to learn a whole new language and legacy models may be translated to CHR.

[1]  R. Sun.  Introduction to Computational Cognitive Modeling , 2007 .

[2]  Matthew F. Rutledge-Taylor.  Can ACT-R Realize “ Newell ’ s Dream ” ? , 2005 .

[3]  W. F. Prokasy,et al.  Classical conditioning II: Current research and theory. , 1972 .

[4]  John R. Anderson,et al.  Implications of the ACT-R Learning Theory: No Magic Bullets , 2000 .

[5]  Javier S. Sainz.  Can ACT-R Realize "Newell's Dream"? , 2005 .

[6]  van Hedderik Rijn,et al.  Proceedings of the Seventh International Conference on Cognitive Modeling , 2006 .

[7]  John R Anderson,et al.  An integrated theory of the mind. , 2004, Psychological review.

[8]  R. Rescorla,et al.  A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement , 1972 .

[9]  Marcello Balduccini,et al.  Formalization of psychological knowledge in answer set programming and its application , 2010, Theory and Practice of Logic Programming.

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

[11]  John R. Anderson.  How Can the Human Mind Occur in the Physical Universe , 2007 .

[12]  John R. Anderson,et al.  Working Memory: Activation Limitations on Retrieval , 1996, Cognitive Psychology.

[13]  Thom W. Frühwirth,et al.  Constraint Handling Rules , 2009, Constraint Programming.

[14]  Frank J. Lee,et al.  Production Compilation: A Simple Mechanism to Model Complex Skill Acquisition , 2003, Hum. Factors.

[15]  Claude Sammut,et al.  PROLOG: A Tutorial Introduction , 1983, Aust. Comput. J..

[16]  Robert L. West.  Deconstructing ACT-R , 2006 .

[17]  Jacob Whitehill,et al.  Understanding ACT-R - an Outsider's Perspective , 2013, ArXiv.

[18]  R. Sun.  The Cambridge Handbook of Computational Psychology: Introduction to Computational Cognitive Modeling , 2008 .

[19]  Ron Sun,et al.  The Cambridge Handbook of Computational Psychology , 2008 .

[20]  Luís Moniz Pereira,et al.  Modelling morality with prospective logic , 2009 .

[21]  John R. Anderson,et al.  Modeling paradigms in ACT-R , 2006 .

[22]  Terrence C. Stewart,et al.  Deconstructing and reconstructing ACT-R: Exploring the architectural space , 2007, Cognitive Systems Research.

[23]  John R. Anderson,et al.  The fan effect: New results and new theories. , 1999 .

[24]  Tom Schrijvers,et al.  Under Consideration for Publication in Theory and Practice of Logic Programming Swi-prolog , 2022 .

[25]  Christian Lebiere,et al.  Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation , 2006 .

[26]  M. F.,et al.  Bibliography , 1985, Experimental Gerontology.

[27]  Tom Schrijvers,et al.  Under Consideration for Publication in Theory and Practice of Logic Programming as Time Goes By: Constraint Handling Rules , 2022 .