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A Decidable Confluence Test for Cognitive Models in ACT-R
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.Comment: To appear in Stefania Costantini, Enrico Franconi, William Van
Woensel, Roman Kontchakov, Fariba Sadri, and Dumitru Roman: "Proceedings of
RuleML+RR 2017". Springer LNC
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