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Predictive ACT-R (PACT-R): Using a physics engine and simulation for physical prediction in a cognitive architecture


Pentecost, D and Sennersten, C and Ollington, R and Lindley, CA and Kang, B, Predictive ACT-R (PACT-R): Using a physics engine and simulation for physical prediction in a cognitive architecture, Proceedings of the 8th International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE 2016), 20-24 March 2016, Rome, Italy, pp. 22-32. ISBN 978-1-61208-462-6 (2016) [Refereed Conference Paper]

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Copyright 2016 IARIA

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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 replicate aspects of human thought and reasoning. The research reported in this paper has developed an enhancement to 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. Inspired by this, the research reported here has developed Predictive ACT-R (PACT-R), based upon integrating a three dimensional (3D) simulation of the AIs environment to allow it to predict, reason about, and then act on, what is happening, or about to happen, in its environment. Here, it is demonstrated by application in an autonomous squash player that the predictive version of ACT-R achieves significantly improved performance compared with the non-predictive version.

Item Details

Item Type:Refereed Conference Paper
Keywords:cognitive architectures, ACT-R, 3D simulation
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Intelligent robotics
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the information and computing sciences
UTAS Author:Pentecost, D (Mr David Pentecost)
UTAS Author:Ollington, R (Dr Robert Ollington)
UTAS Author:Kang, B (Professor Byeong Kang)
ID Code:116496
Year Published:2016
Deposited By:Information and Communication Technology
Deposited On:2017-05-11
Last Modified:2018-02-01

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