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Volume 12 Issue 11
Nov.  2025

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2025  >  12(11): 2175-2193
T.-Y. Chen, W.-N. Chen, F.-F. Wei, X.-Q. Guo, W.-X. Song, R. Zhu, Q. Lin, and J. Zhang, “The confluence of evolutionary computation and multi-agent systems: A survey,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 11, pp. 2175–2193, Nov. 2025. doi: 10.1109/JAS.2025.125246
Citation: T.-Y. Chen, W.-N. Chen, F.-F. Wei, X.-Q. Guo, W.-X. Song, R. Zhu, Q. Lin, and J. Zhang, “The confluence of evolutionary computation and multi-agent systems: A survey,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 11, pp. 2175–2193, Nov. 2025. doi: 10.1109/JAS.2025.125246
shu

The Confluence of Evolutionary Computation and Multi-Agent Systems: A Survey

doi: 10.1109/JAS.2025.125246
Funds:  This work was supported in part by the National Key Research and Development Project (2023YFE0206200), the National Natural Science Foundation of China (U23B2058), in part by Guangdong Regional Joint Foundation Key Project (2022B1515120076), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2025-00555463 & RS-2025-25456394), the Tianjin Top Scientist Studio Project (24JRRCRC00030), and the Tianjin Belt and Road Joint Laboratory (24PTLYHZ00250)
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    Abstract
  • Both evolutionary computation (EC) and multi-agent systems (MAS) study the emergence of intelligence through the interaction and cooperation of a group of individuals. EC focuses on solving various complex optimization problems, while MAS provides a flexible model for distributed artificial intelligence. Since their group interaction mechanisms can be borrowed from each other, many studies have attempted to combine EC and MAS. With the rapid development of the Internet of Things, the confluence of EC and MAS has become more and more important, and related articles have shown a continuously growing trend during the last decades. In this survey, we first elaborate on the mutual assistance of EC and MAS from two aspects, agent-based EC and EC-assisted MAS. Agent-based EC aims to introduce characteristics of MAS into EC to improve the performance and parallelism of EC, while EC-assisted MAS aims to use EC to better solve optimization problems in MAS. Furthermore, we review studies that combine the cooperation mechanisms of EC and MAS, which greatly leverage the strengths of both sides. A description framework is built to elaborate existing studies. Promising future research directions are also discussed in conjunction with emerging technologies and real-world applications.

     

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