KSL-89-35 + redirect page
Algorithms for Bayesian Belief-Network Precomputation + Has identifier
Algorithms for Bayesian Belief-Network Precomputation + Ksl tr id
Algorithms for Bayesian Belief-Network Precomputation + Number
| Algorithms for Bayesian Belief-Network Precomputation |
Bibtype
techreport
Has publishing details
1991
Has title
Algorithms for Bayesian Belief-Network Precomputation
Has where published
KSL-89-35
Has year
1991
Title
Algorithms for Bayesian Belief-Network Precomputation
Year
1991
Abstract
Bayesian belief networks show promise as a … Bayesian belief networks show promise as a representational framework for constructing expert systems; they provide platforms for knowledge acquisition and for normative probabilistic inference. Despite the intuitive appeal of this inference paradigm, the run-time complexity of general belief-network computation may be too great for solving many complex problems in a practical amount of time. Therefore, researchers have focused their attention on developing approximate or special-case algorithms for belief-network inference. For belief networks with a highly skewed distribution of joint probabilities, storing a small number of cases to capture a large proportion of the likely uses of the network may lead to a significant increase in the speed of inference. We report here preliminary results of a set of algorithms that cache (precompute and store) a small subset of a belief network to decrease the expected running time for probability computation. running time for probability computation.
Author
Edward Herskovits and Gregory F. Cooper +
Has author
Edward Herskovits and Gregory F. Cooper +
Has identifier
Algorithms for Bayesian Belief-Network Precomputation +
Institution
Knowledge Systems, AI Laboratory +
Ksl tr id
Algorithms for Bayesian Belief-Network Precomputation +
Number
Algorithms for Bayesian Belief-Network Precomputation +
Process note
YES +
Categories KSL Technical Report +, Publication +, Technical Report +
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