%0 Conference Paper %1 aler:2001:glckg %A Aler, Ricardo %A Borrajo, Daniel %A Isasi, Pedro %B Proceedings of the 2001 Congress on Evolutionary Computation CEC2001 %C COEX, World Trade Center, 159 Samseong-dong, Gangnam-gu, Seoul, Korea %D 2001 %I IEEE Press %K (artificial AI Control EVOCK, Evolution GP GP, Knowledge, PRODIGY, ad-hoc algorithms, approach based blocksworld computational control domain, flexibility, genetic grammar grammars, intelligence), knowledge language language, learning learning, linguistics, mechanisms, of planning problems, programming, restrictions, rule rules, search select space, specific, standard syntax, system, type %P 1220--1227 %T Grammars for Learning Control Knowledge with GP %U http://scalab.uc3m.es/~dborrajo/papers/cec01.ps.gz %X 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 used 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 %@ 0-7803-6658-1

@inproceedings{aler:2001:glckg, 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 used 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}, added-at = {2008-06-19T17:35:00.000+0200}, address = {COEX, World Trade Center, 159 Samseong-dong, Gangnam-gu, Seoul, Korea}, author = {Aler, Ricardo and Borrajo, Daniel and Isasi, Pedro}, biburl = {https://www.bibsonomy.org/bibtex/258273cc28391b14cd9575da2ae479dcd/brazovayeye}, booktitle = {Proceedings of the 2001 Congress on Evolutionary Computation CEC2001}, interhash = {291515621fb6bfa7e580d1d7d2b09f14}, intrahash = {58273cc28391b14cd9575da2ae479dcd}, isbn = {0-7803-6658-1}, keywords = {(artificial AI Control EVOCK, Evolution GP GP, Knowledge, PRODIGY, ad-hoc algorithms, approach based blocksworld computational control domain, flexibility, genetic grammar grammars, intelligence), knowledge language language, learning learning, linguistics, mechanisms, of planning problems, programming, restrictions, rule rules, search select space, specific, standard syntax, system, type}, month = {27-30 May}, notes = {CEC-2001 - A joint meeting of the IEEE, Evolutionary Programming Society, Galesia, and the IEE. IEEE Catalog Number = 01TH8546C, Library of Congress Number = . EVOCK, PRODIGY 4.0, blocksworld}, organisation = {IEEE Neural Network Council (NNC), Evolutionary Programming Society (EPS), Institution of Electrical Engineers (IEE)}, pages = {1220--1227}, publisher = {IEEE Press}, publisher_address = {445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA}, size = {8 pages}, timestamp = {2008-06-19T17:35:31.000+0200}, title = {Grammars for Learning Control Knowledge with {GP}}, url = {http://scalab.uc3m.es/~dborrajo/papers/cec01.ps.gz}, year = 2001 }