ML Anthology

Solving Influence Diagrams Using Gibbs Sampling

Ali Jenzarli
AISTATS 1995 pp. 278-284
/aistats/1995/jenzarli1995aistats-solving/

Abstract

We describe a Monte Carlo method for solving influence diagrams. This method is a combination of stochastic dynamic programming and Gibbs sampling, an iterative Markov chain Monte Carlo algorithm. Our method is especially useful when exact methods for solving influence diagrams fail.

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Text

Jenzarli. "Solving Influence Diagrams Using Gibbs Sampling." Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, 1995.

Markdown

[Jenzarli. "Solving Influence Diagrams Using Gibbs Sampling." Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, 1995.](https://mlanthology.org/aistats/1995/jenzarli1995aistats-solving/)

BibTeX

@inproceedings{jenzarli1995aistats-solving,
  title     = {{Solving Influence Diagrams Using Gibbs Sampling}},
  author    = {Jenzarli, Ali},
  booktitle = {Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics},
  year      = {1995},
  pages     = {278-284},
  volume    = {R0},
  url       = {https://mlanthology.org/aistats/1995/jenzarli1995aistats-solving/}
}