Fostering Cooperation through Dynamic Coalition Formation and Partner Switching

IF 2.2 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

ACM Transactions on Autonomous and Adaptive Systems Pub Date : 2014-03-01 DOI:10.1145/2567928

Ana Peleteiro-Ramallo, J. C. Burguillo, J. Arcos, J. Rodríguez-Aguilar

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引用次数: 34

Abstract

In this article we tackle the problem of maximizing cooperation among self-interested agents in a resource exchange environment. Our main concern is the design of mechanisms for maximizing cooperation among self-interested agents in a way that their profits increase by exchanging or trading with resources. Although dynamic coalition formation and partner switching (rewiring) have been shown to promote the emergence and maintenance of cooperation for self-interested agents, no prior work in the literature has investigated whether merging both mechanisms exhibits positive synergies that lead to increase cooperation even further. Therefore, we introduce and analyze a novel dynamic coalition formation mechanism, that uses partner switching, to help self-interested agents to increase their profits in a resource exchange environment. Our experiments show the effectiveness of our mechanism at increasing the agents’ profits, as well as the emergence of trading as the preferred behavior over different types of complex networks.

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通过动态联盟形成和伙伴转换促进合作

在本文中，我们解决了资源交换环境中自利主体之间合作最大化的问题。我们主要关注的是设计机制，使自利主体之间的合作最大化，使其利润通过与资源的交换或交易而增加。虽然动态联盟形成和伙伴转换(重新布线)已被证明可以促进自利主体合作的出现和维持，但之前的文献中没有研究过合并这两种机制是否会显示出积极的协同效应，从而进一步增加合作。因此，我们引入并分析了一种新的动态联盟形成机制，即利用伙伴交换来帮助自利主体在资源交换环境中增加利润。我们的实验显示了我们的机制在增加代理利润方面的有效性，以及在不同类型的复杂网络中，交易作为首选行为的出现。

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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来源期刊

ACM Transactions on Autonomous and Adaptive Systems 工程技术-计算机：理论方法

CiteScore

4.80

自引率

7.40%

发文量

审稿时长

>12 weeks

期刊介绍： TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community -- and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community - and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. Contributions are expected to be based on sound and innovative theoretical models, algorithms, engineering and programming techniques, infrastructures and systems, or technological and application experiences.