Representing Bayesian Networks within Probabilistic Horn Abduction

📝 Original Info

• Title: Representing Bayesian Networks within Probabilistic Horn Abduction
• ArXiv ID: 1303.5738
• Date: 2013-03-26
• Authors: Researchers from original ArXiv paper

📝 Abstract

This paper presents a simple framework for Horn clause abduction, with probabilities associated with hypotheses. It is shown how this representation can represent any probabilistic knowledge representable in a Bayesian belief network. The main contributions are in finding a relationship between logical and probabilistic notions of evidential reasoning. This can be used as a basis for a new way to implement Bayesian Networks that allows for approximations to the value of the posterior probabilities, and also points to a way that Bayesian networks can be extended beyond a propositional language.

💡 Deep Analysis

Deep Dive into Representing Bayesian Networks within Probabilistic Horn Abduction.

This paper presents a simple framework for Horn clause abduction, with probabilities associated with hypotheses. It is shown how this representation can represent any probabilistic knowledge representable in a Bayesian belief network. The main contributions are in finding a relationship between logical and probabilistic notions of evidential reasoning. This can be used as a basis for a new way to implement Bayesian Networks that allows for approximations to the value of the posterior probabilities, and also points to a way that Bayesian networks can be extended beyond a propositional language.

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