DocumentCode
807923
Title
The Role Of The Lamarck Hypothesis In The Grammatical Evolution Guided By Reinforcement
Author
Mingo, J.M. ; Aler, R.
Author_Institution
Dept. de Inf., Univ. Carlos III de Madrid, Leganes
Volume
6
Issue
6
fYear
2008
Firstpage
500
Lastpage
504
Abstract
Grammatical evolution is an evolutionary algorithm able to develop programs in any language, defined by a grammar. The evolutionary process may be improved if we let the individuals learn during their lifetime. with this aim, the grammatical evolution guided by reinforcement, an algorithm which merges evolution and learning, was created. Grammatical evolution guided by reinforcement uses a Lamarckian mechanism for replacing the original genotypes when a successful learning has occurred. This paper explores the role of the Lamarckian hypothesis. At the same time, grammatical evolution guided by reinforcement is tested in a new domain: autonomous navigation in a Kephera robot simulation.
Keywords
evolutionary computation; grammars; learning (artificial intelligence); IWPAAMS2007-02; Kephera robot simulation; Lamarckian hypothesis; evolutionary algorithm; grammatical evolution; reinforcement learning; Bioinformatics; Biology computing; Evolutionary computation; Genomics; Learning; Navigation; Robots; Surges; Testing; Grammatical Evolution; Lamarck Effect; Reinforcement Learning;
fLanguage
English
Journal_Title
Latin America Transactions, IEEE (Revista IEEE America Latina)
Publisher
ieee
ISSN
1548-0992
Type
jour
DOI
10.1109/TLA.2008.4908181
Filename
4908181
Link To Document