Linear programming for heuristics in optimal planning

Röger, Gabriele and Pommerening, Florian. (2015) Linear programming for heuristics in optimal planning. In: Planning, Search, and Optimization : papers from the 2015 AAAI Workshop ; Austin, Jan. 25-26, 2015. Palo Alto, Calif., pp. 69-76.

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Official URL: http://edoc.unibas.ch/dok/A6390806

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Many recent planning heuristics are based on LP optimization. However, planning experts mostly use LP solvers as a black box and it is often not obvious to them which LP techniques would be most suitable for their specific applications. To foster the communication between the planning and the optimization community, this paper gives an easily accessible overview over these recent LP-based heuristics, namely the optimal cost partitioning heuristic for abstractions, the post-hoc optimization heuristic, a landmark heuristic, the state-equation heuristic, and a delete relaxation heuristic. All these heuristics fit the framework of so-called operator-counting constraints, which we also present.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Artificial Intelligence (Helmert)
UniBasel Contributors:Röger, Gabriele and Pommerening, Florian
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Publisher:AAAI Press
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:16 Oct 2018 13:47
Deposited On:03 Jul 2015 08:53

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