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Abstract: In this paper, we propose a model for solving diagnostic problems based on abductive inference mechanism that uses parsimonious covering theory and add some new features to the general model of diagnostic problem solving. The knowledge pertaining to the model is assumed to be represented in the form of causal chaining, namely, hyperbipartite network. The proposed model is evaluated against the pure abductive reasoning model. The results obtained with the proposed model demonstrate its... (Update)
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BibTeX entry: (Update)
@misc{ using-realistic,
author = "Problem Solving Using",
title = "A Realistic Model For Diagnostic",
url = "citeseer.ist.psu.edu/623903.html" }
Citations (may not include all citations):90 The Computational Complexity of Abduction - Bylander, Allenmang et al. - 1991
90 Abductive Inference Models for Diagnostic Problem-Solving (context) - Peng, Reggia - 1990
62 the Mechanization of Abductive Logic (context) - Pople - 1973
12 A Formal Model of Diagnostic Inference (context) - Reggia, Nau et al. - 1985
9 Diagnostic Problem-Solving with Causal Chaining (context) - Peng, Reggia - 1987
4 ABLOG : Improvements on an Abductive Approach to Diagnostic .. (context) - Goodall, Reggia et al. - 1987
2 Automated Abduction and Machine Learning (context) - O'Rorke - 1988
1 Parsimonious Covering as a Method for Natural Language Inter.. (context) - Dasigi, Reggia - 1989
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