Multi-agent Co-evolutionary Optimization

Multi-Agent Co-Evolutionary Optimization is a computational optimization framework in which multiple distinct agent populations undergo simultaneous evolutionary adaptation, with each population's fitness evaluation inherently dependent on dynamic interactions with others, thereby enabling the emergent co-adaptation of interdependent strategies or solutions.

24

Publications

2.1K

Citations

71

Authors

30

Institutions

Publications per year

2017–2026

7

Authors

71

  1. SS
    Sandip Sen

    University of Tulsa, United States

    2 publications · 74 citations

    2

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  2. EG
    Emile Glorieux

    University West, Sweden

    2 publications · 26 citations

    2

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  3. FD
    Fredrik Danielsson

    University West, Sweden

    2 publications · 26 citations

    2

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  4. BL
    Bengt Lennartson

    Chalmers University of Technology, Sweden

    2 publications · 26 citations

    2

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  5. RD
    Rafał Dreżewski

    AGH University of Krakow, Poland

    2 publications · 54 citations

    2

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1–5 of 71

Venues

  1. Information Sciences

    3 publications · 1.2K citations

    3

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  2. IEEE Access

    2 publications · 36 citations

    2

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  3. Journal of Heuristics

    1 publications · 12 citations

    1

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  4. Soft Computing

    1 publications · 23 citations

    1

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  5. 1

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1–5