Abstract
In this article we describe an approach to the construction of a general learning mechanism based on chunking in Soar. Chunking is a learning mechanism that acquires rules from goal-based experience. Soar is a general problem-solving architecture with a rule-based memory. In previous work we have demonstrated how the combination of chunking and Soar could acquire search-control knowledge (strategy acquisition) and operator implementation rules in both search-based puzzle tasks and knowledge-based expert-systems tasks. In this work we examine the anatomy of chunking in Soar and provide a new demonstration of its learning capabilities involving the acquisition and use of macro-operators.
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Laird, J.E., Rosenbloom, P.S. & Newell, A. Chunking in Soar: The Anatomy of a General Learning Mechanism. Mach Learn 1, 11–46 (1986). https://doi.org/10.1023/A:1022639103969
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DOI: https://doi.org/10.1023/A:1022639103969