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Science / Mathematics / Admissible heuristic / Applied mathematics / Heuristic / Mathematical optimization / Search algorithm / Automated planning and scheduling / Algorithm / Heuristics / Operations research / Heuristic function


Getting the Most Out of Pattern Databases for Classical Planning Florian Pommerening and Gabriele R¨oger and Malte Helmert Universit¨at Basel Basel, Switzerland {florian.pommerening,gabriele.roeger,malte.helmert}@uniba
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City

Toledo / /

Company

Intel / AAAI Press / /

Country

Spain / /

Currency

pence / /

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IndustryTerm

search neighborhood / hill-climbing algorithm / state-space search problems / feasible solution / Any feasible solution / abstraction-based planning systems / domain-independent classical planning systems / classical search domains / iPDB algorithm / heuristic search algorithm / search time / hill-climbing search / search algorithms / /

MarketIndex

IPC / /

Organization

Swiss National Science Foundation / Computational Intelligence / /

Person

Adele Howe / Adi Botea / Yang / Joseph C. Culberson / Silvan Sievers / Sarit Hanan / Blai Bonet / Carlos Linares L´opez / Carmel Domshlak / Ariel Felner / Richard Korf / Sven Koenig / Uzi Zahavi / Maxim Likhachev / Amedeo Cesta / Robert Holte / Jonathan Schaeffer / Malte Helmert / Nathan Sturtevant / Stefan Edelkamp / Ioannis Refanidis / Michael Katz / Manuela Ortlieb / Daniel Borrajo / Patrik Haslum / Wheeler Ruml / Florian Pommerening / /

Position

editor / planner / /

Product

Uzi / /

PublishedMedium

Journal of Artificial Intelligence Research / /

Technology

heuristic search algorithm / hill-climbing algorithm / Xeon E5-2660 processors / artificial intelligence / PDB-based search algorithms / iPDB algorithm / /

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