Multi-Agent Cooperative Pursuit-Evasion Control Using Gene Expression Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8178
- @InProceedings{conf/iecon/NiGHXRL21,
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author = "Yinjie Ni and Shuhua Gao and Sunan Huang and
Cheng Xiang and Qinyuan Ren and Tong Heng Lee",
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title = "Multi-Agent Cooperative Pursuit-Evasion Control Using
Gene Expression Programming",
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booktitle = "IECON 2021, 47th Annual Conference of the IEEE
Industrial Electronics Society",
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year = "2021",
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address = "Toronto, Canada",
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month = "13-16 " # oct,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming, gene
expression programming, pursuit-evasion game, fast
evader",
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isbn13 = "978-1-6654-3554-3",
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bibdate = "2021-11-17",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/iecon/iecon2021.html#NiGHXRL21",
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DOI = "doi:10.1109/IECON48115.2021.9589599",
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size = "6 pages",
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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