Title :
The use of version space controlled genetic algorithms to solve the Boole problem
Author :
Reynolds, Robert G. ; Maletic, Jonathan I. ; Chang, Shan-Ping
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
Abstract :
It is demonstrated that the VGA (version space guided genetic algorithm) is a particular instantiation of a more general class of systems, termed autonomous learning elements (ALEs). The basic components of an ALEs are discussed. The Boole problem posed by S. W. Wilson (1987) is introduced, and its expression in terms of the VGA framework is discussed. The details of the VGA system are given followed by a discussion of results. In particular, the performances of the VGA on two versions of the Boole problem are described and compared with those of classifier systems and decision trees
Keywords :
genetic algorithms; learning systems; problem solving; Boole problem; VGA; autonomous learning elements; classifier systems; decision trees; version space controlled genetic algorithms; Biological cells; Computer science; Cultural differences; Degradation; Genetic algorithms; Genetic mutations; History; Problem-solving; Space exploration; Traveling salesman problems;
Conference_Titel :
Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-8186-2300-4
DOI :
10.1109/TAI.1991.167071