Landmarks Revisited
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Helmert, Malte
Westphal, Matthias
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Dieter Fox and Carla P. Gomes
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Chicago, Illinois, USA
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Abstract
Landmarks for propositional planning tasks are variable assignments that must occur at some point in every solution plan. We propose a novel approach for using landmarks in planning by deriving a pseudo-heuristic and combining it with other heuristics in a search framework. The incorporation of landmark information is shown to improve success rates and solution qualities of a heuristic planner. We furthermore show how additional landmarks and orderings can be found using the information present in multi-valued state variable representations of planning tasks. Compared to previously published approaches, our landmark extraction algorithm provides stronger guarantees of correctness for the generated landmark orderings, and our novel use of landmarks during search solves more planning tasks and delivers considerably better solutions.
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Twenty-Third AAAI Conference on Artificial Intelligence
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© 2008 AAAI Press. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
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Artificial Intelligence and Image Processing not elsewhere classified