面向环境政策制定的模型不确定性下共识群体决策
Consensus group decision making under model uncertainty with a view towards environmental policy making
AI总结：
本文基于 Fréchet 重心提出迭代两阶段共识群体决策方法，并通过聚类处理大型异质群体，用于支持模型不确定性下的环境政策决策。
摘要：
本文提出一种模型不确定性下的共识群体决策方案，该方案由迭代的两阶段程序构成，并基于 Fréchet 重心概念。每一步包括两个阶段：智能体首先通过由其即时交互刻画的局部重心来更新其在意见度量空间中的位置；随后，协调者依据全局重心提出方案，并在每一步检查是否达成共识。对于大型异质群体，该程序可辅以一个初始同质化步骤，即在意见空间中进行聚类，从而形成大型同质群体，并对其应用上述程序。该方案通过受环境经济学启发的示例加以说明。
英文摘要：
In this paper we propose a consensus group decision making scheme under model uncertainty consisting of an iterative two-stage procedure and based on the concept of Fréchet barycenter. Each step consists of two stages: the agents first update their position in the opinion metric space by a local barycenter characterized by the agents' immediate interactions and then a moderator makes a proposal in terms of a global barycenter, checking for consensus at each step. In cases of large heterogeneous groups the procedure can be complemented by an auxiliary initial homogenization step, consisting of a clustering procedure in opinion space, leading to large homogeneous groups for which the aforementioned procedure will be applied. The scheme is illustrated in examples motivated from environmental economics.
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