Urgency coefficient and responsibility coefficient facilitate the evolution of cooperation in multi-agent systems

Zhengwu Zhao; Chunyan Zhang; Jianlei Zhang

doi:10.1117/12.2671143

28 April 2023 Urgency coefficient and responsibility coefficient facilitate the evolution of cooperation in multi-agent systems

Zhengwu Zhao, Chunyan Zhang, Jianlei Zhang

Author Affiliations +

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 1261048 (2023) https://doi.org/10.1117/12.2671143
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Task allocation is a significant topic in the field of artificial intelligence, and ideas for solving this problem are often drawn from the widespread phenomenon of division of labor in nature. For the problem that the existing labor division game model does not match the characteristics of the large-scale division of labor scenarios, we propose a new model named Division of Labor within Community game (DOLC). The article establishes the mathematical model of DOLC, then we investigate the effects of selection intensity, urgency coefficient and responsibility coefficient on the evolution of division of labor. We derived the following conclusions: When both urgency and responsibility coefficients are zero, this causes the tragedy of DOLC, while group has the opportunity to maintain the division of labor if one of them is positive. The responsible group has always been cooperative. Relative to urgency coefficient, responsibility coefficient plays a more noticeable role in facilitating the evolution of cooperation in population. DOLC model is well suited to task allocation problem in multi-agent systems, and the findings of this article provide new insights for improving the intelligence of unmanned systems and optimizing task allocation and scheduling.

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Zhengwu Zhao, Chunyan Zhang, and Jianlei Zhang "Urgency coefficient and responsibility coefficient facilitate the evolution of cooperation in multi-agent systems", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 1261048 (28 April 2023); https://doi.org/10.1117/12.2671143

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KEYWORDS

Systems modeling

Mathematical modeling

Robots

Fire

Intelligence systems

Artificial intelligence

Biology

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