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Abstract: Planning by Rewriting (PbR) is a new paradigm for efficient high-quality planning that exploits plan rewriting rules and e#cient local search techniques to transform an easy-to-generate, but possibly suboptimal, initial plan into a high-quality plan. Despite the advantages of PbR in terms of scalability, plan quality, and anytime behavior, PbR requires the user to define a set of domain-specific plan rewriting rules which can be di#cult and time-consuming. This paper presents an... (Update)
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BibTeX entry: (Update)
@misc{ institute-jose,
author = "Information Sciences Institute",
title = "Jose Luis Ambite, Craig A. Knoblock Steven Minton",
url = "citeseer.ist.psu.edu/765514.html" }
Citations (may not include all citations):482 Combinatorial Optimization: Algorithms and Complexity (context) - Papadimitriou, Steiglitz - 1982
417 Local Search in Combinatorial Optimization (context) - Aarts, Lenstra - 1997
130 Extending planning graphs to an ADL subset - Koehler, Nebel et al. - 1997
87 A robust and fast action selection mechanism for planning - Bonet, Loerincs et al. - 1997
80 A reinforcement learning approach to job-shop scheduling - Zhang, Dietterich - 1995
68 Learning Search Control Knowledge: An Explanation-Based Appr.. (context) - Minton - 1988
64 UCPOP: A sound (context) - Penberthy, Weld - 1992
60 and replanning for information gathering (context) - Knoblock - 1995
58 Acquiring search-control knowledge via static analysis - Etzioni - 1993
51 the complexity of blocks-world planning - Gupta, Nau - 1992
37 Automatically configuring constraint satisfaction programs: .. - Minton - 1996
29 Lazy incremental learning of control knowledge for e#ciently.. - Borrajo, Veloso - 1997
26 Solving complex planning tasks through extraction of subprob.. - Koehler - 1998
23 Integrating abstraction and explanation-based learning in PR.. - Knoblock, Minton et al. - 1991
20 Failure driven dynamic search control for partial order plan.. - Kambhampati, Katukam et al. - 1996
16 Learning to improve constraint-based scheduling (context) - Zweben, Davis et al. - 1992
15 Planning by Rewriting - Ambite - 1998
14 Flexible and scalable query planning in distributed and hete.. - Ambite, Knoblock - 1998
11 Small is beautiful: A brute-force approach to learning first.. - Minton, Underwood - 1994
9 Planning by rewriting: E#ciently generating high-quality pla.. (context) - Ambite, Knoblock - 1997
5 Learning to improve both e#ciency and quality of planning (context) - Estlin, Mooney - 1997
5 Representing and learning qualityimproving search control kn.. (context) - Perez - 1996
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