Propagation of 2-Monotone Lower Probabilities on an Undirected Graph

2013/02/13 by Lonnie Chrisman, Chrisman, Lonnie
Computer Science · Decision Sciences · Mathematics · #Artificial Intelligence (cs.AI) #Artificial intelligence #Bayesian Modeling and Causal Inference #Choquet integral #Combinatorics #Computer science #Decomposition #Discrete mathematics #FOS: Computer and information sciences #Graph #Graphical model #Marginal distribution #Mathematics #Monotone polygon #Multi-Criteria Decision Making #Random variable #Representation (politics) #Rough Sets and Fuzzy Logic #Statistics #Undirected graph #Upper and lower bounds #cs.AI

paper · pdf · doi:10.48550/arxiv.1302.3569

Appears in Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI1996)

arxiv created 2013/02/13 · openalex publication_date 2013/02/13 · arxiv updated 2013/02/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Lower and upper probabilities, also known as Choquet capacities, are widely used as a convenient representation for sets of probability distributions. This paper presents a graphical decomposition and exact propagation algorithm for computing marginal posteriors of 2-monotone lower probabilities (equivalently, 2-alternating upper probabilities).

Citations

• Independence with Lower and Upper Probabilities
• A New Approach to Updating Beliefs
• Quasi-Bayesian Strategies for Efficient Plan Generation: Application to the Planning to Observe Problem
• Complexity of Finding Embeddings in a k-Tree
• A Mathematical Theory of Evidence

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