论文信息 - First-Order Bayesian Reasoning

First-Order Bayesian Reasoning

This paper briefly discusses problems with traditional Bayesian networks, and previous attempts at overcoming those problems, as a motivation for formulating a first-order knowledge based approach to Bayesian inference. The proposed first-order knowledge based approach endeavours to address each of the traditional Bayesian network problems.

Dale A. Lambert | Ingrid Fabian

[1] Peter Haddawy,et al. Answering Queries from Context-Sensitive Probabilistic Knowledge Bases , 1997, Theor. Comput. Sci..

[2] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .

[3] Peter Haddawy,et al. Generating Bayesian Networks from Probablity Logic Knowledge Bases , 1994, UAI.

[4] Fahiem Bacchus. Using First-Order Probability Logic for the Construction of Bayesian Networks , 1993, UAI.

[5] Richard E. Neapolitan,et al. Probabilistic reasoning in expert systems - theory and algorithms , 2012 .

[6] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[7] Peter Haddawy,et al. Probabilistic Logic Programming and Bayesian Networks , 1995, ASIAN.

[8] Sabine Glesner,et al. Constructing Flexible Dynamic Belief Networks from First-Order Probalistic Knowledge Bases , 1995, ECSQARU.