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Author: Antoni Ligęza

Affiliation: AGH - University of Science and Technology, Poland

ISBN: 978-989-758-158-8

Keyword(s): Abduction, Constraint Programming, Model-based Diagnosis, Consistency-based Reasoning.

Related Ontology Subjects/Areas/Topics: Applications and Case-studies ; Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Domain Analysis and Modeling ; Health Engineering and Technology Applications ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Symbolic Systems

Abstract: Abduction can be considered as a principal way of reasoning for problem solving. Abductive inference consists in generation of hypotheses which explain — or logically imply — the phenomenon under investigation in view of accessible background knowledge and are consistent with all other observations. Looking for such hypotheses is typically performed with a spectrum of trial-and-error or search methods and tools. In case of purely logical statements the hypotheses take the form of a set of facts, both positive and negative ones. For example, in case of model based diagnostic reasoning, such diagnostic hypotheses can be generated by consistency based reasoning with minimal search effort. In more complex cases, where values of certain variables are to be found, pure backtracking search becomes inefficient. In this paper we attempt to put forward such abductive inference into a formal framework of Constraint Programming in order to enable the use of constraint propagation techniques. The main idea behind this approach is to make abduction more constructive. The discussion is illustrated with a diagnostic example of a multiplier-adder system. (More)

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Paper citation in several formats:
Ligęza, A. (2015). Towards Constructive Abduction - Solving Abductive Problems with Constraint Programming.In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015) ISBN 978-989-758-158-8, pages 352-357. DOI: 10.5220/0005625603520357

@conference{keod15,
author={Antoni Ligęza.},
title={Towards Constructive Abduction - Solving Abductive Problems with Constraint Programming},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015)},
year={2015},
pages={352-357},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005625603520357},
isbn={978-989-758-158-8},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015)
TI - Towards Constructive Abduction - Solving Abductive Problems with Constraint Programming
SN - 978-989-758-158-8
AU - Ligęza, A.
PY - 2015
SP - 352
EP - 357
DO - 10.5220/0005625603520357

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