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
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;
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
DOI :
10.1109/TLA.2008.4908181