Abstract

This paper presents a view of planning as a task supported by a dynamic memory. This view attempts to integrate models of memory, learning and planning into a single system that learns about planning by creating new plans and analyzing how they interact with the world. We call this view of planning Case-Based Planning. A case-based planner makes use of its own past experience in developing new plans. It relies on its memory of observed effects, rather than a set of causal rules, to create and modify new plans. Memories of past successes are accessed and modified to create new plans. Memories of past failures are used to warn the planner of impending problems, and memories of past repairs are called upon to tell the planner how to how to deal with them. This view of planning from experience supports and is supported by a learning system that incorporates new experiences into the planner's episodic memory. This learning algorithm gains from the planner's failures as well as its successe...

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