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

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发表于 2025-3-21 18:29:23 | 显示全部楼层 |阅读模式
书目名称Local Search for Planning and Scheduling
副标题ECAI 2000 Workshop,
编辑Alexander Nareyek
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Local Search for Planning and Scheduling; ECAI 2000 Workshop,  Alexander Nareyek Conference proceedings 2001 Springer-Verlag Berlin Heidelb
出版日期Conference proceedings 2001
关键词AI Planning; Evolutionary Algorithms; Local Search; Planning Algorithms; Planning Graphs; Search Algorith
版次1
doihttps://doi.org/10.1007/3-540-45612-0
isbn_softcover978-3-540-42898-5
isbn_ebook978-3-540-45612-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2001
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发表于 2025-3-21 20:14:13 | 显示全部楼层
Incremental Local Search for Planning Problemsn plan, the third stage guarantees the completeness and optimality of the generated solution and the fourth stage, a partial-order planner, completes the process by finding the missing actions of the final solution plan, if any.
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Empirical Evaluation of Local Search Methods for Adapting Planning Policies in a Stochastic Environmthe heuristic sets and show that the two chosen local search algorithms perform well. We present empirical data that suggests this is due to smoothness properties of the search space for the search algorithms.
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The GRT Planner: New Resultsnd automatic irrelevant objects elimination, are presented. Finally, the planner has been equipped with a hill-climbing strategy and a closed list of visited states for pruning purposes. Performance results show that GRT exhibits significant improvement over its AIPS-00 competition version.
发表于 2025-3-22 14:48:11 | 显示全部楼层
Alexander NareyekIncludes supplementary material:
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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 problems, mainly those for planning and scheduling.
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