Task Search and Allocation Strategy for Heterogeneous Multiagent Systems Under Communication Constraints

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2024-11-19 DOI:10.1109/TSMC.2024.3491595
Zehui Mao;Donghao Liu;Kai Ju;Bin Jiang;Xing-Gang Yan
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Abstract

In this article, a novel task search and allocation strategy is developed for heterogeneous multiagent systems with limited search range and communication constraints, which includes three processes: 1) task search; 2) task allocation; and 3) formation recovery. In order to optimize task search efficiency under communication constraints, a multigroup task search strategy is proposed by minimizing the average overlap degree between agents’ search ranges, which divides agents into multiple groups and establishes intragroup communication links. According to the communication link and group allocation results, an optimal search formation is designed for each group to maximize their individual search ranges. For transmitting information between different groups, by employing the agent with the highest communication efficiency within the discovery agent’s group as the relay agent, a communication relay strategy is proposed to transmit the task information to other groups. Then, a task allocation strategy based on communication relays is designed to achieve global task allocation by using the estimated state information of all agents. Moreover, to ensure the sustainability of task search and allocation, an intergroup scheduling strategy is proposed to recover the optimal search formation after agents complete the task-related works. Simulation results verify the effectiveness of the proposed task search and allocation strategy.
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通信约束下异构多智能体系统的任务搜索与分配策略
本文针对有限搜索范围和通信约束的异构多智能体系统,提出了一种新的任务搜索和分配策略,该策略包括三个过程:1)任务搜索;2)任务分配;3)地层采收率。为了优化通信约束下的任务搜索效率,提出了一种最小化智能体搜索范围平均重叠度的多组任务搜索策略,将智能体划分为多个组,并建立组内通信链路。根据通信链路和分组分配结果,为每个分组设计最优搜索队形,使各自的搜索范围最大化。对于不同组之间的信息传递,采用发现代理所在组内通信效率最高的代理作为中继代理,提出了一种将任务信息传递到其他组的通信中继策略。然后,设计了一种基于通信中继的任务分配策略,利用所有agent的估计状态信息实现全局任务分配。此外,为了保证任务搜索和分配的可持续性,提出了一种群间调度策略,在智能体完成任务相关工作后恢复最优搜索编队。仿真结果验证了所提任务搜索与分配策略的有效性。
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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Table of Contents Table of Contents IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors IEEE Systems, Man, and Cybernetics Society Information
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