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An approximate Pareto optimal cooperative negotiation model for multiple continuous dependent issues

机译：多个连续相关问题的近似Pareto最优合作谈判模型

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摘要

Cooperative negotiation is proved to be an effective paradigm to solve complex dynamic multi-objective problems in which each objective is associated to an agent. When the multi-objective problem is defined on several continuous variables, cooperative negotiation can be traced back to a sequential bargaining. However, the complexity of highly reconfigurable scenarios with a large number of agents does not allow the adoption of classical game theory techniques to design optimal bargaining models for cooperative negotiations. A way to tackle this complexity is based on the decentralization of the system, usually obtained by introducing a mediator that reduces the amount of information directly exchanged between the agents. In this paper we present and experimentally evaluate a decentralized bargaining model for cooperative negotiation on multiple continuous dependent issues able to produce approximate Pareto optimal outcomes.
机译：实践证明，合作谈判是解决复杂的动态多目标问题的有效范例，在复杂的动态多目标问题中，每个目标都与一个主体相关联。当在多个连续变量上定义多目标问题时，合作谈判可以追溯到顺序谈判。但是，具有大量代理的高度可重新配置的场景的复杂性不允许采用经典博弈论技术来设计用于合作谈判的最佳议价模型。解决这种复杂性的方法是基于系统的分散性，通常通过引入减少代理之间直接交换的信息量的介体来获得。在本文中，我们提出并通过实验评估了用于多个连续因果问题的合作谈判的分散议价模型，这些问题能够产生近似的帕累托最优结果。

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