Inference in Belief Network using Logic Sampling and Likelihood Weighing algorithms

Advances in Distributed Computing and Artificial Intelligence Journal

K. S. JASMINE¹  Gavani PRATHVIRAJ S.²  P Ijantakar RAJASHEKAR²  K. A. SUMITHRA DEVI² 

[1] BISITE Research Group;RV College of Engineering;

关键词: belief network;    logic sampling;    likelihood weighing;    dynamic decision making;    uncertainty;   

DOI  :  10.14201/ADCAIJ20142617

来源: DOAJ

【 摘 要 】

Over the time in computational history, belief networks have become an increasingly popular mechanism for dealing with uncertainty in systems. It is known that identifying the probability values of belief network nodes given a set of evidence is not amenable in general. Many different simulation algorithms for approximating solution to this problem have been proposed and implemented. This paper details the implementation of such algorithms, in particular the two algorithms of the belief networks namely Logic sampling and the likelihood weighing are discussed. A detailed description of the algorithm is given with observed results. These algorithms play crucial roles in dynamic decision making in any situation of uncertainty.

【 授权许可】

Unknown