将公平融入利益冲突的无限重复博弈中,消除冲突

Jianye Hao, Ho-fung Leung
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引用次数: 1

摘要

在许多多智能体应用中,博弈论可以作为一个有用的工具来建模这些多智能体场景,并分析智能体之间的策略交互。公平是资源分配、作业调度等多智能体应用中需要考虑的一个重要目标,但传统博弈论并未考虑公平问题。然而,在许多情况下,传统博弈论中的纯策略或混合策略纳什均衡的解决概念可能导致不公平和低效的结果。本文从人类行为中的公平动机出发,在无限重复博弈的背景下,明确地引入了公平策略的概念。研究表明,在利益冲突的无限重复博弈中,使用公平策略不仅可以使代理获得相等的收益(实现公平),而且可以使代理的收益总和最大化(实现效率)。更重要的是,我们证明了这对理想的公平策略是一种新的均衡-公平策略均衡,从而为智能体做出决策并与其他智能体甚至人类进行协调提供了直观的解决方案概念。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incorporating Fairness into Infinitely Repeated Games with Conflicting Interests for Conflicts Elimination
In many multi-agent applications, game theory can serve as a useful tool to model these multi-agent scenarios and analyse the strategic interactions among agents. Fairness is an important goal to consider in a variety of multi-agent applications such as resource allocation or job scheduling problems, but it is not taken into consideration in traditional game theory. However, in many cases the solution concepts of pure strategy or mixed strategy Nash equilibria from traditional game theory can lead to unfair and inefficient outcomes. In this paper, we explicitly introduce the concept of fairness strategy in the context of infinitely repeated game inspired from fairness motive observed in human behaviors. We show that using fairness strategy, not only the agents can receive equal payoffs (achieving fairness) but also the sum of their payoffs is maximized (achieving efficiency) in the infinitely repeated games with conflicting interests. More importantly, we prove that this desirable pair of fairness strategies is in a new type of equilibrium - fairness strategy equilibrium, which thus provides an intuitive solution concept for the agents to make their decisions and coordinate with other agents or even humans.
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