MCE Reasoning in Recursive Causal Networks

📝 Original Info

• Title: MCE Reasoning in Recursive Causal Networks
• ArXiv ID: 1304.2380
• Date: 2013-04-10
• Authors: Researchers from original ArXiv paper

📝 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.

💡 Deep Analysis

Deep Dive into MCE Reasoning in Recursive Causal Networks.

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.

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Reference