A comparative analysis of Horn models and Bayesian Networks for diagnosis

Luigi PORTINALE; P. TORASSO

doi:10.1007/3-540-63576-9_113

A comparative analysis of Horn models and Bayesian Networks for diagnosis

Luigi PORTINALE
, P. TORASSO

Department of Science and Technological Innovation

Research output: Contribution to conference › Paper › peer-review

Abstract

The aim of the paper is to formally relate logical Horn models and Bayesian Networks (BNs) in the framework of diagnostic reasoning. This is pursued by pointing out similarities between the two formalisms at the modeling level and by introducing into BNs a suitable notion of derivation. We also discuss modeling issues underlying the choice of Horn-based models vs BNs, by making explicit the “completion semantics” underlying a BN. This correspondence between “completed” Horn theories and BNs allows us to formally justify classical diagnostic schemata adopted for BNs.

Original language	English
Pages	254-265
Number of pages	12
DOIs	https://doi.org/10.1007/3-540-63576-9_113
Publication status	Published - 1997
Event	5th Congress of the Italian Association for Artificial Intelligence (AI*IA-97) - Roma, Italy Duration: 1 Jan 1997 → …

Conference

Conference	5th Congress of the Italian Association for Artificial Intelligence (AI*IA-97)
City	Roma, Italy
Period	1/01/97 → …

Keywords

Horn models
Bayesian Networks

Access to Document

10.1007/3-540-63576-9_113

http://hdl.handle.net/11579/9428

Cite this

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A comparative analysis of Horn models and Bayesian Networks for diagnosis

Abstract

Conference

Keywords

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