Abstract
Case-based planning is an approach to planning where previous planning experience stored in a case base provides guidance to solving new problems. Such a guidance can be extremely useful when the new problem is very hard to solve, or the stored previous experience is highly valuable (because, e.g., it was provided and/or validated by human experts) and the system should try to reuse it as much as possible. However, as known in general case-based reasoning, the case base needs to be maintained at a manageable size, in order to avoid that the computational cost of querying it excessively grows, making the entire approach ineffective. We formally define the problem of case base maintenance for planning, discuss which criteria should drive a successful policy to maintain the case base, introduce some policies optimizing different criteria, and experimentally analyze their behavior by evaluating their effectiveness and performance.
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