Title :
Granular jointree probability propagation
Author :
Butz, C.J. ; Lingras, P.
Author_Institution :
Dept. of Comput. Sci., Regina Univ., Sask., Canada
Abstract :
Jointree computation continues to be central to the theory and practice of probabilistic expert systems. Recent research has incorporated granular structures to facilitate propagation in the jointree. In this paper, we propose a method for granular jointree probability propagation. Our method extends the previous works by allowing the granular levels to communicate with each other. It is explicitly demonstrated that our granular approach increases the amount of parallelism during probability propagation.
Keywords :
Markov processes; belief networks; expert systems; probabilistic logic; probability; trees (mathematics); Bayesian network; directed acyclic graph; granular jointree probability propagation; granular structures; hierarchical Markov network; jointree computation; parallel computation; probabilistic expert systems; Bayesian methods; Computer science; Concurrent computing; Expert systems; Inference algorithms; Markov random fields; Parallel processing; Probability distribution;
Conference_Titel :
Fuzzy Information, 2004. Processing NAFIPS '04. IEEE Annual Meeting of the
Print_ISBN :
0-7803-8376-1
DOI :
10.1109/NAFIPS.2004.1336251
