DocumentCode
2617755
Title
Some experiments on the use of genetic algorithms in a Boltzmann machine
Author
Bellgard, Matthew I. ; Tsang, Chi Ping
Author_Institution
Dept. of Comput. Sci., Univ. of Western Australia, Nedlands, WA, Australia
fYear
1991
fDate
18-21 Nov 1991
Firstpage
2645
Abstract
The authors combined a genetic algorithm (GA) and simulated annealing to form a genetic Boltzmann machine (GBM) and attempted to understand the properties of such an architecture by experiments. Results of other experiments are also shown relating to the selection of parameters for the GA. The effects of population, different crossover point operators, and hidden units are illustrated. It is concluded that with careful design a GBM can perform nearly as well as a Boltzmann machine in a scalar computer. However, the GBM is easily amenable to parallel computation
Keywords
genetic algorithms; neural nets; simulated annealing; crossover point operators; genetic Boltzmann machine; genetic algorithms; hidden units; neural nets; simulated annealing; Artificial intelligence; Australia; Computer science; Convergence; Genetic algorithms; Intelligent networks; Laboratories; Logic; Neural networks; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170327
Filename
170327
Link To Document