Titlebook: Local Search for Planning and Scheduling; ECAI 2000 Workshop, Alexander Nareyek Conference proceedings 2001 Springer-Verlag Berlin Heidelb

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978-3-540-42898-5Springer-Verlag Berlin Heidelberg 2001

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https://doi.org/10.1007/3-540-45612-0AI Planning; Evolutionary Algorithms; Local Search; Planning Algorithms; Planning Graphs; Search Algorith

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Meta-heuristics: The State of the Arteering, economics and science in reasonable time horizons. In this paper we give some insight into the state of the art of meta-heuristics. This primarily focuses on the significant progress which general frames within the meta-heuristics field have implied for solving combinatorial optimization pro

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Lagrange Multipliers for Local Search on Planning Graphstasks. The space of the local search is formed by particular subgraphs of a planning graph representing partial plans. The operators for moving from one search state to the next one are graph modification operations corresponding to adding (deleting) actions to (from) a partial plan. GPG can use dif

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Beyond the Plan-Length Criterionare related to these resources and must take this into account in planning their behavior. In the field of artificial intelligence, resource-based action planning systems have recently begun to mushroom. However, these systems still tend to neglect resources. Conventional plan length is the primary

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