Distributed Distributive Justice

David Burth Kurka, J. Pitt
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引用次数: 9

Abstract

Some open systems must address a standard resource allocation problem: how to collectivise and distribute a set of common-pool resources, with respect to multiple criteriasuch as fairness, inclusivity and sustainability. Previous work in self-organising multi-agent systems formalised Nicholas Rescher's theory of distributive justice so that agents could self-organise the allocation according to contextualised legitimate claims. However, although this presented a viable solution in principle, in practicethe process contained two 'expensive' voting rounds and an(albeit elected) centralised 'head' role, compromising parallelism, scalability and security. This in turn could be a hindrance to its application in large, real-life systems. In this paper, we propose an alternative solution to the problem, based on direct interaction between agents in a decentralised manner. Instead of voting, we develop an autonomous mechanism of trust and reputation calculated independently by each agent from its local observationsand interactions. Simulations demonstrate the efficiencyand effectiveness of the new solution to find fair allocations indiverse scenarios, including situations with non-compliant agents. Moreover, the effect of topology on our algorithms capacity isexamined, showing that it is possible to achieve fair solutions even when agents do not have direct access to the whole network.
分配正义
一些开放系统必须解决一个标准的资源分配问题:如何在考虑公平性、包容性和可持续性等多重标准的情况下,对一组公共资源进行集体化和分配。先前关于自组织多智能体系统的研究将尼古拉斯·雷舍的分配正义理论形式化了,这样智能体就可以根据情境化的合法要求来自组织分配。然而,尽管这在原则上提出了一个可行的解决方案,但在实践中,该过程包含两个“昂贵的”投票轮和一个(尽管是选举产生的)集中的“头”角色,损害了并行性、可扩展性和安全性。这反过来又会阻碍其在大型现实系统中的应用。在本文中,我们提出了一种基于代理之间以分散方式直接交互的替代解决方案。代替投票,我们开发了一种信任和声誉的自治机制,由每个代理根据其本地观察和交互独立计算。仿真结果验证了该方法在不同情况下(包括不服从代理的情况)寻找公平分配的效率和有效性。此外,研究了拓扑对算法能力的影响,表明即使代理不能直接访问整个网络,也有可能获得公平的解决方案。
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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