Improving Delete Relaxation Heuristics Through Explicitly Represented Conjunctions

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Improving Delete Relaxation Heuristics Through Explicitly Represented Conjunctions

Heuristic functions based on the delete relaxation compute upper and lower bounds on the optimal delete-relaxation heuristic h, and are of paramount importance in both optimal and satisficing planning. Here we introduce a principled and flexible technique for improving h, by augmenting delete-relaxed planning tasks with a limited amount of delete information. This is done by introducing special...

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Heuristic search is one of the most successful approaches to classical planning, finding solution paths in large state spaces. A major focus has been the development of domainindependent heuristic functions. One recent method are partial delete relaxation heuristics, improving over the standard delete relaxation heuristic through imposing a set C of conjunctions to be treated as atomic. Practic...

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Heuristic search using heuristics extracted from the delete relaxation is one of the most effective methods in planning. Since finding the optimal solution of the delete relaxation is intractable, various heuristics introduce independence assumptions, the implications of which are not yet fully understood. Here we use concepts from graph theory to show that in problems with unary action precond...

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ژورنال

عنوان ژورنال: Journal of Artificial Intelligence Research

سال: 2014

ISSN: 1076-9757

DOI: 10.1613/jair.4277