AAAI Publications, 2011 AAAI Fall Symposium Series

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A Case Study in Integrating Probabilistic Decision Making and Learning in a Symbolic Cognitive Architecture: Soar Plays Dice
John Edwin Laird, Nate Derbinsky, Miller Tinkerhess

Last modified: 2011-11-03

Abstract


One challenge for cognitive architectures is to effectively use different forms of knowledge and learning. We present a case study of Soar agents that play a multiplayer dice game, in which probabilistic reasoning and heuristic symbolic knowledge appear to play a central role. We develop and evaluate a collection of agents that use different combinations of probabilistic decision making, heuristic symbolic reasoning, opponent modeling, and learning. We demonstrate agents that use Soar’s rule learning mechanism (chunking) to convert deliberate reasoning with probabilities into implicit reasoning, and then use reinforcement learning to further tune performance.

Keywords


Cognitive architecture; reinforcement learning; decision making under uncertainty; Soar

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