Shortest path based decision making using probabilistic inference

• 主要作者: Akshat KUMAR
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2016
• 主題: Artificial intelligence; Bayesian networks; Budget control; Decision making; Graph theory; Integer programming; Maximum principle; Message passing; Mixtures; Optimization; Artificial Intelligence and Robotics; Operations Research, Systems Engineering and Industrial Engineering; Theory and Algorithms
• 在線閱讀: https://ink.library.smu.edu.sg/sis_research/3396; https://ink.library.smu.edu.sg/context/sis_research/article/4397/viewcontent/ShortestPathBasedDecisionMaking.pdf
• 機構: Singapore Management University

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem...