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Can We Reach Pareto Optimal Outcomes Using Bottom-Up Approaches?

机译：我们可以使用自下而上的方法达到帕累托最优的结果吗？

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摘要

Classically, disciplines like negotiation and decision making have focused on reaching Pareto optimal solutions due to its stability and efficiency properties. Despite the fact that many practical and theoretical algorithms have successfully attempted to provide Pareto optimal solutions, they have focused on attempting to reach Pareto Optimality using horizontal approaches, where optimality is calculated taking into account every participant at the same time. Sometimes, this may prove to be a difficult task (e.g., conflict, mistrust, no information sharing, etc.). In this paper, we explore the possibility of achieving Pareto Optimal outcomes in a group by using a bottom-up approach: discovering Pareto optimal outcomes by interacting in subgroups. We analytically show that the set of Pareto optimal outcomes in a group covers the Pareto optimal outcomes within its subgroups. This theoretical finding can be applied in a variety of scenarios such as negotiation teams, multi-party negotiation, and team formation to social recommendation. Additionally, we empirically test the validity and practicality of this proof in a variety of decision making domains and analyze the usability of this proof in practical situations.
机译：传统上，谈判和决策等学科都因其稳定性和效率特性而专注于达到帕累托最优解决方案。尽管许多实践和理论算法都已成功尝试提供Pareto最优解，但他们仍专注于尝试使用水平方法来达到Pareto最优性，在这种方法中，同时考虑到每个参与者都计算出了最优性。有时，这可能证明是一项艰巨的任务（例如，冲突，不信任，没有信息共享等）。在本文中，我们探索了使用自下而上的方法在小组中实现帕累托最优结果的可能性：通过在子组中进行交互来发现帕累托最优结果。我们分析地表明，一组中的帕累托最优结果涵盖了其子组内的帕累托最优结果。这一理论发现可以应用于各种场景，例如谈判团队，多方谈判以及团队推荐给社会。此外，我们在各种决策领域中通过经验测试了该证明的有效性和实用性，并分析了该证明在实际情况下的可用性。

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