Fair payoff distribution in multiagent systems under Pareto optimality

Thananchai Khamket, Chattrakul Sombattheera
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Abstract

This research proposes a set of algorithms to compute fair payoff distribution among agents in service composition domain based on their contribution. In our system, intelligent agents, representing service providers, negotiate among themselves and form composite services to satisfy multiple-objective requirements. The quality of service for each objective is measured in term of degree of satisfaction. The overall quality of service is achieved by maximizing requesters satisfaction on all objectives according to Pareto optimality. We then deploy Shapley Value concept for fair payoff distribution among agents based on their contributions to the requesters optimal satisfaction. Since the computational complexity for Shapley Value is exponential, we are interested in investigating how well the algorithms for computing payoff perform. We found that on a typical computer, the algorithm can cope with around 20 agents with reasonable computational time.
Pareto最优下多智能体系统的公平收益分配
本研究提出了一套基于贡献计算服务组合领域中agent间公平收益分配的算法。在我们的系统中,智能代理代表服务提供者相互协商,形成复合服务,以满足多目标需求。每个目标的服务质量都是用满意度来衡量的。根据帕累托最优性,通过最大化请求者对所有目标的满意度来实现整体服务质量。然后根据代理人对请求者最优满意度的贡献,运用Shapley值概念进行报酬公平分配。由于Shapley值的计算复杂度是指数级的,我们有兴趣研究计算收益的算法的性能。我们发现,在一台典型的计算机上,该算法可以在合理的计算时间内处理大约20个代理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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