DocumentCode
3250818
Title
Grammars for learning control knowledge with GP
Author
Aler, Ricardo ; Borrajo, Daniel ; Isasi, Pedro
Author_Institution
Univ. Carlos III de Madrid, Spain
Volume
2
fYear
2001
fDate
2001
Firstpage
1220
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
Keywords
computational linguistics; genetic algorithms; grammars; learning (artificial intelligence); search problems; AI planning system; EVOCK; Evolution of Control Knowledge; GP based system; PRODIGY; ad-hoc mechanisms; blocksworld domain; control knowledge learning; control rule language; control rule syntax; control rules; genetic programming; grammar approach flexibility; grammar specific; grammars; language restrictions; search space; standard GP; standard select type; Artificial intelligence; Control systems; Learning systems; Performance evaluation; Problem-solving; Protection; Strain control; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location
Seoul
Print_ISBN
0-7803-6657-3
Type
conf
DOI
10.1109/CEC.2001.934330
Filename
934330
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