Evaluation of Bayesian networks with flexible state-space abstraction methods

2002/05/01 by Chao-Lin Liu, Chao Lin Liu, Michael P. Wellman · 1 citation
Computer Science · Mathematics · #AI-based Problem Solving and Planning #Abstraction #Algorithm #Artificial intelligence #Bayesian Modeling and Causal Inference #Bayesian network #Bayesian probability #Computer science #Exploit #Heuristics #Machine Learning and Algorithms #Mathematical optimization #Mathematics #Property (philosophy) #Space (punctuation) #State (computer science) #State space #Statistics #Theoretical computer science

paper · pdf · doi:10.1016/s0888-613x(01)00067-6

crossref issued 2002/05/01 · crossref published 2002/05/01 · crossref published-print 2002/05/01 · openalex publication_date 2002/05/01 · crossref created 2002/07/25 · crossref deposited 2020/01/08 · crossref indexed 2022/03/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03

Citations

• Computational Complexity Reduction for BN2O Networks Using Similarity of States
• Approximations in Bayesian Belief Universe for Knowledge Based Systems
• Computing Upper and Lower Bounds on Likelihoods in Intractable Networks
• Context-Specific Approximation in Probabilistic Inference
• On Information and Sufficiency
• The computational complexity of probabilistic inference using bayesian belief networks
• Approximating probabilistic inference in Bayesian belief networks is NP-hard
• An optimal approximation algorithm for Bayesian inference
• Refinement and Coarsening of Bayesian Networks
• Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (1998)
• Topological Parameters for Time-Space Tradeoff

Cited by

• Granular computing [wikipedia]