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Purely declarative action descriptions are overrated: classical planning with simulators

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dc.contributor.author Francès, Guillem
dc.contributor.author Ramírez Jávega, Miquel
dc.contributor.author Lipovetzky, Nir
dc.contributor.author Geffner, Héctor
dc.date.accessioned 2018-03-12T10:50:11Z
dc.date.available 2018-03-12T10:50:11Z
dc.date.issued 2017
dc.identifier.citation Francès G, Ramírez M, Lipovetzky N, Geffner H. Purely declarative action descriptions are overrated: classical planning with simulators. In: IJCAI 2017. Twenty-Sixth International Joint Conference on Artificial Intelligence; 2017 Aug 19-25; Melbourne, Australia. [California]: IJCAI; 2017. p. 4294-301. DOI: 10.24963/ijcai.2017/600
dc.identifier.uri http://hdl.handle.net/10230/34087
dc.description Comunicació presentada a la Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI 2017), celebrada els dies 19 a 25 d'agost a Melbourne, Austràlia.
dc.description.abstract Classical planning is concerned with problems where a goal needs to be reached from a known initial state by doing actions with deterministic, known effects. Classical planners, however, deal only with classical problems that can be expressed in declarative planning languages such as STRIPS or PDDL. This prevents their use on problems that are not easy to model declaratively or whose dynamics are given via simulations. Simulators do not provide a declarative representation of actions, but simply return successor states. The question we address in this paper is: can a planner that has access to the structure of states and goals only, approach the performance of planners that also have access to the structure of actions expressed in PDDL? To answer this, we develop domain-independent, black box planning algorithms that completely ignore action structure, and show that they match the performance of state-of-the-art classical planners on the standard planning benchmarks. Effective black box algorithms open up new possibilities for modeling and for expressing control knowledge, which we also illustrate.
dc.description.sponsorship G. Francès is supported by the M. de Maeztu Programme (MDM-2015-0502) and H. Geffner by grant TIN2015-67959-P, both from MINECO, Spain. M. Ramirez and N. Lipovetzky have been partially funded by the Australian DST Group.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher International Joint Conferences on Artificial Intelligence Organization (IJCAI)
dc.relation.ispartof IJCAI 2017. Twenty-Sixth International Joint Conference on Artificial Intelligence; 2017 Aug 19-25; Melbourne, Australia. [California]: IJCAI; 2017. p. 4294-301.
dc.rights Copyright © 2017 International Joint Conferences on Artificial Intelligence
dc.title Purely declarative action descriptions are overrated: classical planning with simulators
dc.type info:eu-repo/semantics/conferenceObject
dc.identifier.doi http://dx.doi.org/10.24963/ijcai.2017/600
dc.subject.keyword Planning and scheduling: planning algorithms
dc.subject.keyword Planning and scheduling: search in planning and scheduling
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2015-67959-P
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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