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David E. Foulser

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AIJ Journal 1992 Journal Article

Theory and algorithms for plan merging

David E. Foulser
Ming Li
Qiang Yang

Merging operators in a plan can yield significant savings in the cost to execute a plan. This paper provides a formal theory for plan merging and presents both optimal and efficient heuristic algorithms for finding minimum cost merged plans. The optimal plan merging algorithm applies a dynamic programming method to handle multiple linear plans and is extended to partially ordered plans in a novel way. Furthermore, with worst-case and average-case complexity analysis and empirical tests, we demonstrate that efficient and well-behaved approximation algorithms are applicable for optimizing plans with large sizes.

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AAAI Conference 1991 Conference Paper

A Quantitative Theory for Plan Merging

David E. Foulser

Merging operators in a plan can yield significant savings in the cost to execute a plan. Past research in planning has concentrated on handling harmful interactions among plans, but the understanding of positive ones has remained at a qualitative, heuristic level. This paper provides a quantitative study for plan optimization and presents both optimal and approximate algorithms for finding minimum-cost merged plans. With worst and average case complexity analysis and empirical tests, we demonstrate that efficient and wellbehaved approximation algorithms are applicable for optimizing general plans with large sizes.

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