A Domain-Independent Algorithm for Multi-Plan Adaptation and Merging in Least Commitment Planners

Anthony G. Francis, Jr. and Ashwin Ram

Solving problems in many real-world domains requires integrating knowledge from several past experiences. This integration requires the dynamic retrieval of multiple experiences and the extraction of their relevant subparts. Our solution is the Multi-Plan Adaptor (MPA), a method for merging partial-order plans in the context of case-based least-commitment planning. MPA provides this ability by extracting an intermediate goal statement from a partial plan, clipping a stored plan to the intermediate goal statement, and then splicing the clipping into the original partial plan. MPA is implemnted in the NICOLE multistrategy reasoning system, where it is paired with MOORE, an asynchronous, resource-bounded memory module. MOORE initially retrieves its current "best guess" but continues search, spontaneously returning a better retrieval as soon as it is found.


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