Stochastic Simulation of Bayesian Belief Networks

  title={Stochastic Simulation of Bayesian Belief Networks},
  author={Homer L. Chin and Gregory F. Cooper},
  journal={Int. J. Approx. Reasoning},
This paper examines Bayesian belief network inference using simulation as a method for computing the posterior probabilities of network variables. Specifically, it examines the use of a method described by Henrion, called logic sampling, and a method described by Pearl, called stochastic simulation. We first review the conditions under which logic sampling is computationally infeasible. Such cases motivated the development of the Pearl's stochastic simulation algorithm. We have found that this… CONTINUE READING
Recent Discussions
This paper has been referenced on Twitter 3 times over the past 90 days. VIEW TWEETS
13 Citations
11 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 11 references

Probabilistic inference using belief networks is NP - hard

  • GF Cooper
  • 1987

NESTOR : A computer - based medical diagnostic aid that integrates causal and probabilistic knowledge

  • Cooper GF.
  • 1984

A model - based method for computer - aided medical decision making

  • CA WeissSM.Kulikowski, S Amarel, A Safir
  • Artificial Intelligence
  • 1978

A method for computing probabilities in complex situations

  • WF Rousseau
  • 1968

Similar Papers

Loading similar papers…