Multi-Agent Cooperative Pursuit-Evasion Control Using Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8194

@InProceedings{conf/iecon/NiGHXRL21,

• author = "Yinjie Ni and Shuhua Gao and Sunan Huang and Cheng Xiang and Qinyuan Ren and Tong Heng Lee",
• title = "Multi-Agent Cooperative Pursuit-Evasion Control Using Gene Expression Programming",
• booktitle = "IECON 2021, 47th Annual Conference of the IEEE Industrial Electronics Society",
• year = "2021",
• address = "Toronto, Canada",
• month = "13-16 " # oct,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, gene expression programming, pursuit-evasion game, fast evader",
• isbn13 = "978-1-6654-3554-3",
• bibdate = "2021-11-17",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/iecon/iecon2021.html#NiGHXRL21",
• DOI = "doi:10.1109/IECON48115.2021.9589599",
• size = "6 pages",
• abstract = "This paper works on multiple-pursuer single-evader (MPSE) problems with a fast evader, which means multiple pursuers try to capture one evader while the evader tries to escape from the encirclement. The biggest concern is that the maximum velocity of the evader is larger than all the pursuers. Some improved strategies for the evader and pursuers based on traditional algorithms are firstly provided. Then gene expression programming (GEP) is used to generate new strategies which are better than the traditional ones. This paper shows configurations of function set, terminal set, fitness, evaluation function, and other parameters used in the GEP method, which can be implemented in other cases or similar problems.",

}

Genetic Programming entries for Yinjie Ni Shuhua Gao Sunan Huang Cheng Xiang Qinyuan Ren Tong Heng Lee

Citations