Hostname: page-component-6898cfcb55-kwdml Total loading time: 0 Render date: 2026-11-11T21:25:49.927Z Has data issue: false hasContentIssue false
  • English
  • Français

Exchanging Conflict Resolution in an Adaptable Implementation of ACT-R

Published online by Cambridge University Press:  21 July 2014

DANIEL GALL and
THOM FRÜHWIRTH
DANIEL GALL
Affiliation:
Faculty of Engineering and Computer Science, Ulm University, Germany (e-mail: daniel.gall@uni-ulm.de, thom.fruehwirth@uni-ulm.de)
THOM FRÜHWIRTH
Affiliation:
Faculty of Engineering and Computer Science, Ulm University, Germany (e-mail: daniel.gall@uni-ulm.de, thom.fruehwirth@uni-ulm.de)
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

In computational cognitive science, the cognitive architecture ACT-R is very popular. It describes a model of cognition that is amenable to computer implementation, paving the way for computational psychology. Its underlying psychological theory has been investigated in many psychological experiments, but ACT-R lacks a formal definition of its underlying concepts from a mathematical-computational point of view. Although the canonical implementation of ACT-R is now modularized, this production rule system is still hard to adapt and extend in central components like the conflict resolution mechanism (which decides which of the applicable rules to apply next).

In this work, we present a concise implementation of ACT-R based on Constraint Handling Rules which has been derived from a formalization in prior work. To show the adaptability of our approach, we implement several different conflict resolution mechanisms discussed in the ACT-R literature. This results in the first implementation of one such mechanism. For the other mechanisms, we empirically evaluate if our implementation matches the results of reference implementations of ACT-R.

Keywords

computational cognitive modelingcomputational psychologyACT-RConstraint Handling Rulesproduction rule systemsconflict resolution

Information

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 14 , Special Issue 4-5: 30th International Conference on Logic Programming , July 2014, pp. 525 - 538
Copyright
Copyright © Cambridge University Press 2014 

References

ACT-R 2014. The ACT-R Homepage. http://act-r.psy.cmu.edu/ Google Scholar
ACT-R Tutorial 2004. The ACT-R 5.0 tutorial. http://act-r.psy.cmu.edu/tutorials-5-0/ Google Scholar
Anderson, J. R. 2007. How can the human mind occur in the physical universe? Oxford University Press.CrossRefGoogle Scholar
Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., and Qin, Y. 2004. An integrated theory of the mind. Psychological Review 111, 4, 1036–1060.CrossRefGoogle ScholarPubMed
Anderson, J. R. and Lebiere, C. 1998. The Atomic Components of Thought. Lawrence Erlbaum Associates, Inc.Google Scholar
Belavkin, R. 2005. Optimist conflict resolution overlay for the ACTR cognitive architecture. http://www.eis.mdx.ac.uk/staffpages/rvb/software/optimist/optimist-for-actr.pdf Google Scholar
Belavkin, R. and Ritter, F. E. 2004. Optimist: A new conflict resolution algorithm for act-r. In ICCM. 40–45.Google Scholar
Bothell, D. ACT-R 6.0 Reference Manual – Working Draft. Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.Google Scholar
Frühwirth, T. 2009. Constraint Handling Rules. Cambridge University Press.CrossRefGoogle Scholar
Gall, D. 2013. A rule-based implementation of ACT-R using constraint handling rules. Master Thesis, Ulm University.Google Scholar
jACT-R. Benefits of jACT-R (part of the FAQ section of the homepage). http://jactr.org/node/50 Google Scholar
jACT-R. The Homepage of jACT-R. http://jactr.org/ Google Scholar
McDermott, J. and Forgy, C. 1977. Production system conflict resolution strategies. SIGART Bull. 63 (June), 37–37.CrossRefGoogle Scholar
Rescorla, R. A. and Wagner, A. W. 1972. A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. Appleton-Century-Crofts, New York, Chapter 3, 64–99.Google Scholar
Salvucci, D. About ACT-R: The Java Simulation & Development Environment. http://cog.cs.drexel.edu/act-r/about.html Google Scholar
Salvucci, D. ACT-R: The Java Simulation & Development Environment – Homepage. http://cog.cs.drexel.edu/act-r/ Google Scholar
Stewart, T. C. and West, R. L. 2006. Deconstructing ACT-R. In Proceedings of the Seventh International Conference on Cognitive Modeling. 298–303.Google Scholar
Stewart, T. C. and West, R. L. 2007. Deconstructing and reconstructing ACT-R: exploring the architectural space. Cognitive Systems Research 8, 3 (Sept.), 227–236.CrossRefGoogle Scholar
Sun, R. 2008. Introduction to computational cognitive modeling. In The Cambridge Handbook of Computational Psychology, Sun, R., Ed. Cambridge University Press, New York, 3–19.Google Scholar
Taatgen, N. A. and Anderson, J. R. 2002. Why do children learn to say broke? a model of learning the past tense without feedback. Cognition 86, 2, 123–155.CrossRefGoogle Scholar
Taatgen, N. A., Lebiere, C., and Anderson, J. 2006. Modeling paradigms in ACT-R. In Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press, 29–52.Google Scholar
Young, R. M. 2003. Should ACT-R include production refraction? In Proceedings of 10th Annual ACT-R Workshop.Google Scholar
Supplementary material: PDF

GALL and FRÜHWIRTH

Exchanging Conflict Resolution in an Adaptable Implementation of ACT-R

Download GALL and FRÜHWIRTH(PDF)
PDF 121.1 KB