Bounded recursive decomposition: A search-based method for belief-network inference under limited resources

DOI10.1016/0888-613X(96)00012-6zbMath0941.68765OpenAlexW2073205103MaRDI QIDQ1809340

Gregory F. Cooper, Stefano Monti

Publication date: 20 December 1999

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0888-613x(96)00012-6

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (3)

Methods for constructing balanced elimination trees and other recursive decompositions ⋮ Anytime anyspace probabilistic inference ⋮ A Monte Carlo algorithm for probabilistic propagation in belief networks based on importance sampling and stratified simulation techniques

Uses Software

• NESTOR

Cites Work

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• Fusion, propagation, and structuring in belief networks
• Approximating probabilistic inference in Bayesian belief networks is NP- hard
• Evidential reasoning using stochastic simulation of causal models
• Fusion and propagation with multiple observations in belief networks
• The computational complexity of probabilistic inference using Bayesian belief networks
• Current research directions in the development of expert systems based on belief networks
• Decision Analytic Networks in Artificial Intelligence
• A randomized approximation algorithm for probabilistic inference on bayesian belief networks

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