A Decidable Confluence Test for Cognitive Models in ACT-R View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2017

AUTHORS

Daniel Gall , Thom Frühwirth

ABSTRACT

Computational cognitive modeling investigates human cognition by building detailed computational models for cognitive processes. Adaptive Control of Thought – Rational (ACT-R) is a rule-based cognitive architecture that offers a widely employed framework to build such models. There is a sound and complete embedding of ACT-R in Constraint Handling Rules (CHR). Therefore analysis techniques from CHR can be used to reason about computational properties of ACT-R models. For example, confluence is the property that a program yields the same result for the same input regardless of the rules that are applied. In ACT-R models, there are often cognitive processes that should always yield the same result while others e.g. implement strategies to solve a problem that could yield different results. In this paper, a decidable confluence criterion for ACT-R is presented. It allows to identify ACT-R rules that are not confluent. Thereby, the modeler can check if his model has the desired behavior. The sound and complete translation of ACT-R to CHR from prior work is used to come up with a suitable invariant-based confluence criterion from the CHR literature. Proper invariants for translated ACT-R models are identified and proven to be decidable. The presented method coincides with confluence of the original ACT-R models. More... »

PAGES

119-134

References to SciGraph publications

  • 2016. Translation of Cognitive Models from ACT-R to Constraint Handling Rules in RULE TECHNOLOGIES. RESEARCH, TOOLS, AND APPLICATIONS
  • 2017-01. On proving confluence modulo equivalence for Constraint Handling Rules in FORMAL ASPECTS OF COMPUTING
  • 2007. Observable Confluence for Constraint Handling Rules in LOGIC PROGRAMMING
  • 2007. Graph Transformation Systems in CHR in LOGIC PROGRAMMING
  • Book

    TITLE

    Rules and Reasoning

    ISBN

    978-3-319-61251-5
    978-3-319-61252-2

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-61252-2_9

    DOI

    http://dx.doi.org/10.1007/978-3-319-61252-2_9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1090045925


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