English

MCE Reasoning in Recursive Causal Networks

Artificial Intelligence 2013-04-10 v1

Abstract

A probabilistic method of reasoning under uncertainty is proposed based on the principle of Minimum Cross Entropy (MCE) and concept of Recursive Causal Model (RCM). The dependency and correlations among the variables are described in a special language BNDL (Belief Networks Description Language). Beliefs are propagated among the clauses of the BNDL programs representing the underlying probabilistic distributions. BNDL interpreters in both Prolog and C has been developed and the performance of the method is compared with those of the others.

Keywords

Cite

@article{arxiv.1304.2380,
  title  = {MCE Reasoning in Recursive Causal Networks},
  author = {Wilson X. Wen},
  journal= {arXiv preprint arXiv:1304.2380},
  year   = {2013}
}

Comments

Appears in Proceedings of the Fourth Conference on Uncertainty in Artificial Intelligence (UAI1988)

R2 v1 2026-06-21T23:56:05.258Z