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A multi-issue negotiation protocol among agents with nonlinear utility functions

机译:具有非线性效用函数的智能体之间的多问题协商协议

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Multi-Issue Negotiation protocols have been studied very widely and represent a promising field since most of negotiation problems in the real-world are complex ones including multiple issues. In particular, in reality issues are constrained each other. This makes agents' utilities nonlinear. There have been a lot of work on multi-issue negotiations. However, there have been very few work that focus on nonlinear utility spaces. In this paper, we assume agents have nonlinear utility spaces. For the linear utility domain, agents can aggregate the utilities of the issue-values by simple linear summation. In the real world, such aggregations are unrealistic. For example, we cannot just add up the value of car's tires and the value of car's engine when engineers design a car. In this paper, we propose an auction-based multiple-issue negotiation protocol among nonlinear utility agents. Our negotiation protocol employs several techniques, i.e., adjusting sampling, auction-based maximization of social welfare. Our experimental results show that our method can outperform the existing simple methods in particular in the huge utility space that can be often found in the real-world. Further, theoretically, our negotiation protocol can guarantee the completeness if some conditions are satisfied.
机译:由于现实世界中的大多数协商问题都是复杂的,包括多个问题,因此,多问题协商协议已经得到了广泛的研究,代表了一个有前途的领域。特别是,实际上,问题是相互制约的。这使得代理的效用是非线性的。关于多问题谈判,有很多工作。但是,很少有工作专注于非线性效用空间。在本文中,我们假设主体具有非线性效用空间。对于线性效用域,代理可以通过简单的线性求和来汇总发行值的效用。在现实世界中,这种聚合是不现实的。例如,当工程师设计汽车时,我们不能仅仅将汽车轮胎的价值和汽车发动机的价值相加。在本文中,我们提出了一种在非线性效用代理之间基于拍卖的多问题协商协议。我们的谈判协议采用多种技术,即调整抽样,基于拍卖的社会福利最大化。我们的实验结果表明,我们的方法可以胜过现有的简单方法,特别是在现实世界中经常发现的巨大效用空间中。此外,从理论上讲,如果满足某些条件,我们的协商协议可以保证完整性。

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