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A Direct Reputation Model for VO Formation

机译:VO形成的直接声誉模型

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摘要

We show that reputation is a basic ingredient in the Virtual Organisation (VO) formation process. Agents can use their experiences gained in direct past interactions to model other's reputation and deciding on either join a VO or determining who is the most suitable set of partners. Reputation values are computed using a reinforcement learning algorithm, so agents can learn and adapt their reputation models of their partners according to their recent behaviour. Our approach is especially powerful if the agent participates in a VO in which the members can change their behaviour to exploit their partners. The reputation model presented in this paper deals with the questions of deception and fraud that have been ignored in current models of VO formation.
机译:我们证明信誉是虚拟组织(VO)形成过程中的基本要素。座席可以利用从过去的直接互动中获得的经验来建立他人的声誉模型,并决定加入VO或确定谁是最合适的伙伴。使用强化学习算法计算信誉值,因此座席可以根据其最近的行为来学习和调整其伙伴的信誉模型。如果代理人参加VO,会员可以更改其行为以利用其合作伙伴,则我们的方法特别有效。本文介绍的声誉模型处理的欺骗和欺诈问题在当前的VO形成模型中已被忽略。

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