Using a physics engine in ACT-R to aid decision making

Advanced Cognitive Technologies can use cognitive architectures as a basis for higher level reasoning in Artificial Intelligence (AI). Adaptive Control of Thought – Rational (ACT-R) is one such cognitive architecture that attempts to simulate aspects of human thought and reasoning. The research reported in this paper has developed an enhancement to Adaptive Control of Thought – Rational (ACT-R) that will allow greater understanding of the environment the AI is situated in. Former research has shown that humans perform simple mental simulations to predict the outcomes of events when faced with complex physical problems. The method has been demonstrated by application in an autonomous squash player for which predictive version of ACT-R achieves significantly improved performance compared with the non-predictive version.