Title :
Genetic network programming - application to intelligent agents
Author :
Katagiri, H. ; Hirasama, K. ; Hu, J.
Author_Institution :
Graduate Sch. of Inf. Sci. & Eng. Sci., Kyushu Univ., Fukuoka, Japan
Abstract :
Recently many studies have been made on the automatic design of complex systems using evolutionary optimization techniques such as genetic algorithms (GA), evolution strategy (ES), evolutionary programming (EP) and genetic programming (GP). It is generally recognized that these techniques are very useful for optimizing fairly complex systems such as the generation of intelligent behavior sequences of robots. A new method, genetic network programming (GNP), is proposed in order to acquire these behavior sequences efficiently. GNP is composed of plural nodes for agents to execute simple judgment/processing and they are connected with each other to form a network structure. Agents behave according to the contents of the nodes and their connections in GNP. In order to obtain a better structure, the GNP changes itself using evolutionary optimization techniques
Keywords :
evolutionary computation; genetic algorithms; multi-agent systems; planning (artificial intelligence); behavior sequences; complex systems; evolution strategy; evolutionary optimization; evolutionary programming; genetic algorithms; genetic network programming; genetic programming; intelligent agents; intelligent behavior sequences; judgment; Algorithm design and analysis; Automatic programming; Design optimization; Economic indicators; Genetic algorithms; Genetic programming; Intelligent agent; Intelligent robots; Robot programming; Robotics and automation;
Conference_Titel :
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location :
Nashville, TN
Print_ISBN :
0-7803-6583-6
DOI :
10.1109/ICSMC.2000.886607