HKUST Library Institutional Repository Banner

HKUST Institutional Repository >
Computer Science and Engineering >
CSE Conference Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/757
Title: A simple approach to Bayesian network computations
Authors: Zhang, Nevin Lianwen
Poole, David
Keywords: Reasoning under uncertainty
Bayesian networks
Algorithm
Issue Date: 1994
Citation: Proceedings of the 10th Canadian conference on artificial intelligence, Banff, Alberta, Canada, May 1994
Abstract: The general problem of computing posterior probabilities in Bayesian networds is NP-hard (Cooper 1990). However efficient algorithms are often possible for particular applications by exploiting problem structures. It is well understood that the key to the materialization of such a possibility is to make use of conditional independence and work with factorizations of joint probabilities rather than joint probabilities themselves. Differnent exact approaches can be characterized in terms of their choices of factorizations. We propose a new approach which adopts a straightforward way for factorizing joint probabilities. In comparison with the clique tree propagation approach, our approach is very simple. It allows the pruning of irrelevant variables, it accommodates changes to the knowledge base more easily. It is easier to implement. More importantly, it can be adapted to utilize both intercausal independence and conditional independence in one uniform framework. On the other hand, clique tree propagation is better in terms of facilitating pre-computations.
URI: http://hdl.handle.net/1783.1/757
Appears in Collections:CSE Conference Papers

Files in This Item:

File Description SizeFormat
canai94.pdf170KbAdobe PDFView/Open

All items in this Repository are protected by copyright, with all rights reserved.