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http://dx.doi.org/10.9723/jksiis.2022.27.2.061

Approximation Algorithm for Multi Agents-Multi Tasks Assignment with Completion Probability  

Kim, Gwang (조선대학교 경영학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.27, no.2, 2022 , pp. 61-69 More about this Journal
Abstract
A multi-agent system is a system that aims at achieving the best-coordinated decision based on each agent's local decision. In this paper, we consider a multi agent-multi task assignment problem. Each agent is assigned to only one task and there is a completion probability for performing. The objective is to determine an assignment that maximizes the sum of the completion probabilities for all tasks. The problem, expressed as a non-linear objective function and combinatorial optimization, is NP-hard. It is necessary to design an effective and efficient solution methodology. This paper presents an approximation algorithm using submodularity, which means a marginal gain diminishing, and demonstrates the scalability and robustness of the algorithm in theoretical and experimental ways.
Keywords
Multi-agent system; Task assignment problem; approximation algorithm; Submodularity; Combinatorial optimization;
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