ORIGINAL RESEARCH article
Front. Phys.
Sec. Social Physics
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1617607
This article is part of the Research TopicReal-World Applications of Game Theory and Optimization, Volume IIIView all 4 articles
Multi-agent task allocation method based on cost-effectiveness maximization multi-round auction algorithm
Provisionally accepted
- 1North China Institute of Science and Technology, Tangshan, Hebei Province, China
- 2University of Science and Technology Beijing, Beijing, China
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In task driven multi-agent autonomous collaboration technology, agents collaborate to complete tasks based on their characteristics. How to comprehensively consider the performance of agents and the requirements of tasks to allocate tasks to agents is crucial for multi-agent autonomous collaboration technology. This paper proposes a distributed multi round auction algorithm FMMRA that maximizes task cost-effectiveness, in response to the current application of auction algorithms to solve multi-agent task allocation problems without considering the relationship between agents and task characteristics, as well as the issue of not considering the benefits of task holders.First, the concept of task fitness is introduced, that is, the comprehensive adaptability of agents to multiple attributes of tasks. The relative importance weight of task attributes is determined according to the analytic hierarchy process, and the fitness function is constructed. Secondly, a dynamic bidding strategy was introduced to enhance the bid received by the task holder from the agent. Finally, the concept of cost-effectiveness is proposed, and the cost-effectiveness of agent is introduced into the buyer matching rule. The cost-effectiveness of agent is defined as the weighted sum of the fitness of agent to task and the bid of agent to task. The cost-effectiveness of a task is defined as the sum of the cost-effectiveness of all agents executing the task. The problem of maximizing task cost-effectiveness is the problem of maximizing the returns of task holders. An analysis was conducted on the characteristics of the proposed multi round auction algorithm in terms of incentive compatibility, individual rationality, and computational efficiency from a theoretical perspective. Experimental validation was conducted on the algorithm proposed in this paper.
Keywords: task allocation, Multi-agent, auction game, task fitness, task cost-effectiveness
Received: 24 Apr 2025; Accepted: 17 Jun 2025.
Copyright: © 2025 Zhou, Lan, Yang, Wang, Li, Li and Lyu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Guowei Li, North China Institute of Science and Technology, Tangshan, Hebei Province, China
Ting Lyu, University of Science and Technology Beijing, Beijing, China
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