题　目：An MILP-Based Solution Scheme for Factored and Robust Factored Markov Decision Processes

嘉　宾：Wolfram Wiesemann, 教授，帝国理工学院

主持人：许欢 教授 上海交通大学安泰经济与管理学院

时　间：2025年6月4日（周三）16:00-17:30

地　点：线上腾讯会议（会议ID：409-473-368，密码：123456，链接：https://meeting.tencent.com/dm/nuoUlURKV66H），线下会场：安泰楼A507室

内容简介：

Factored Markov decision processes (MDPs) are a prominent paradigm within the artificial intelligence community for modeling and solving large-scale MDPs whose rewards and dynamics decompose into smaller, loosely interacting components. Through the use of dynamic Bayesian networks and context-specific independence, factored MDPs can achieve an exponential reduction in the state space of an MDP and thus scale to problem sizes that are beyond the reach of classical MDP algorithms. However, factored MDPs are typically solved using custom-designed algorithms that can require meticulous implementations and considerable fine-tuning. In this talk, we propose a mathematical programming approach to solving factored MDPs. In contrast to existing solution schemes, our approach leverages off-the-shelf solvers, which allows for a streamlined implementation and maintenance; it effectively capitalizes on the factored structure present in both state and action spaces; and it readily extends to the largely unexplored class of robust factored MDPs, whose transition kernels are only known to reside in a pre-specified ambiguity set. Our numerical experiments demonstrate the potential of our approach.

演讲人简介：

Wolfram Wiesemann is Professor of Analytics & Operations as well as the head of the Analytics, Marketing & Operations department at Imperial College Business School. His research interests evolve around decision-making under uncertainty, with applications to supply chain management, healthcare and energy. Wolfram is an elected member of the boards of the Mathematical Optimization Society and the Stochastic Programming Society, and he currently serves as editor in-chief of Operations Research Letters as well as a department co-editor for Management Science.

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