We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main contribution is to show how classic representation theorems from social choice theory can be adapted to characterize optimal policies in this dynamic setting. We provide an axiomatic characterization of MDP reward functions that agree with the Utilitarianism social welfare functionals of social choice theory. We also provide discussion of cases when the implementation of social choice-theoretic axioms may fail to lead to long-run optimal outcomes.

中文翻译：

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偏好变化的社会选择：表示定理和长期政策

我们将不断变化的偏好作为马尔可夫决策过程来研究群体决策。随着时间的推移，在为一群人做出选择时，自动化决策系统越来越流行，这激励着我们。我们的主要贡献是展示了社会选择理论中的经典表示定理如何适用于描述这种动态环境中的最优政策。我们提供了与社会选择理论的功利主义社会福利函数一致的 MDP 奖励函数的公理化特征。我们还讨论了社会选择理论公理的实施可能无法导致长期最佳结果的情况。