The study of a new multiagent-based genetic algorithm

Autor:	Yue-Jin Tan, Ji Li, Hong-Zhong Deng
Rok vydání:	2003
Předmět:	Meta-optimization Computer science business.industry Cultural algorithm Population-based incremental learning Quality control and genetic algorithms Genetic algorithm Artificial intelligence Genetic representation Genetic operator business Evaluation function
Zdroj:	Proceedings. International Conference on Machine Learning and Cybernetics.
DOI:	10.1109/icmlc.2002.1167398
Popis:	Through the analysis and studying of the simple genetic algorithm (SGA) and its research state, the authors suggest a new multiagent-based genetic algorithm, define the environment of SGA, present the agent structure, genetic operator, target/evaluation function, and flow chat. Finally, they verify this new GA with two test functions. The results show that this new GA have many merits and advantages.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::52be07db3fbb864129cf876971f33404 https://doi.org/10.1109/icmlc.2002.1167398 Zobrazit plný text záznamu