Grammars for learning control knowledge with GP

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dc.contributor.author Aler, Ricardo
dc.contributor.author Borrajo Millán, Daniel
dc.contributor.author Isasi, Pedro
dc.date.accessioned 2009-04-22T14:35:19Z
dc.date.available 2009-04-22T14:35:19Z
dc.date.issued 2001-05
dc.identifier.bibliographicCitation Proceedings of the 2001 Congress on Evolutionary Computation, (CEC 2001). vol.2, p. 1220-1227
dc.identifier.isbn 0-7803-6657-3
dc.identifier.uri http://hdl.handle.net/10016/4028
dc.description Congress on Evolutionary Computation, 2001. Seul, 27-30 May 2001
dc.description.abstract In standard GP there are no constraints on the structure to evolve: any combination of functions and terminals is valid. However, sometimes GP is used to evolve structures that must respect some constraints. Instead of “ad-hoc” mechanisms, grammars can be used to guarantee that individuals comply with the language restrictions. In addition, grammars permit great flexibility to define the search space. EVOCK (Evolution of Control Knowledge) is a GP based system that learns control rules for PRODIGY, an AI planning system. EVOCK uses a grammar to constrain individuals to PRODIGY 4.0 control rule syntax. The authors describe the grammar specific details of EVOCK. Also, the grammar approach flexibility has been used to extend the control rule language utilized by EVOCK in earlier work. Using this flexibility, tests were performed to determine whether using combinations of several types of control rules for planning was better than using only the standard select type. Experiments have been carried out in the blocksworld domain that show that using the combination of types of control rules does not get better individuals, but it produces good individuals more frequently.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE
dc.rights © IEEE
dc.title Grammars for learning control knowledge with GP
dc.type conferenceObject
dc.type bookPart
dc.relation.publisherversion http://dx.doi.org/10.1109/CEC.2001.934330
dc.subject.eciencia Informática
dc.identifier.doi 10.1109/CEC.2001.934330
dc.rights.accessRights openAccess
dc.relation.eventdate 27-30 May 2001
dc.relation.eventplace Seoul (South Korea)
dc.relation.eventtitle Congress on Evolutionary Computation, CEC 2001
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 1220
dc.identifier.publicationlastpage 1227
dc.identifier.publicationtitle Proceedings of the 2001 Congress on Evolutionary Computation, (CEC 2001)
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