Efficiency improvement of imitation operator in multi-agent control model based on Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Hara:2016:IWCIA,

• author = "Akira Hara and Hiroki Konishi and Jun-ichi Kushida and Tetsuyuki Takahama",
• title = "Efficiency improvement of imitation operator in multi-agent control model based on Cartesian Genetic Programming",
• booktitle = "2016 IEEE 9th International Workshop on Computational Intelligence and Applications",
• year = "2016",
• editor = "Shimpei Matsumoto and Tomoko Tateyam",
• pages = "69--74",
• address = "Hiroshima",
• month = "5 " # nov,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, Cartesian genetic programming",
• DOI = "doi:10.1109/IWCIA.2016.7805751",
• abstract = "In this paper, we focus on evolutionary optimization of multi-agent behaviour. In our previous work, we have proposed a multi-agent control model based on Cartesian Genetic Programming (CGP). In CGP, each individual is represented by a graph-structural program. The CGP has a characteristics that each individual has multiple output nodes. Therefore, by assigning the outputs to respective agents, we can control multiple agents by an individual. The method enables multiple agents to not only take different actions according to their own roles but also share sub-programs if the same behaviour is needed for solving problems. In addition, a new genetic operator for multi-agent control, imitation operator, has been proposed to facilitate the grouping of agents. An agent selects another agent at random for imitating the behavior. However, if the number of agents increases, the appropriate agent cannot always be selected for imitation. Therefore, in this paper, we propose a modified imitation operator for selecting useful agent. We applied our method to a food foraging problem. The experimental results showed that the performance of our method is superior to those of the conventional models.",
• notes = "http://www.smc-hiroshima.info.hiroshima-cu.ac.jp/events/iwcia/2016/contr_program.html

  Graduate School of Information Sciences, Hiroshima City University, 3-4-1, Ozuka-higashi, Asaminami-ku, Hiroshima, Japan 731-3194

  Also known as \cite{7805751}",

}

Genetic Programming entries for Akira Hara Hiroki Konishi Jun-ichi Kushida Tetsuyuki Takahama

Citations