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KI - Künstliche Intelligenz
Published in: KI - Künstliche Intelligenz 1/2019

17-12-2018 | Dissertation and Habilitation Abstracts

Dissertation Abstract: Qualitative Rational Reasoning with Finite Conditional Knowledge Bases

Theoretical and Implementational Aspects

Author: Christian Eichhorn

Published in: KI - Künstliche Intelligenz | Issue 1/2019

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Abstract

Inferring prior unknown knowledge from the information given is a core task of the discipline knowledge representation and reasoning in (symbolic) artificial intelligence. With conditionals as building blocks of knowledge bases, inductive methods generate epistemic states on which inference relations are defined. This thesis recalls established approaches to these tasks, and both researches them and compares them based on formal properties. It uses network approaches to make the tasks of generating and storing the results easier, and researches the applicability of formal methods to the results of psychological studies to model human reasoning. In recalling techniques like the so called OCF-networks and Inference Patterns, this dissertation abstract provides a brief view into these topics.
previous article Intentional Forgetting Must be Part of the Functionality
next article Concepts and Algorithms for Computing Maximum Entropy Distributions for Knowledge Bases with Relational Probabilistic Conditionals

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Metadata
Title
Dissertation Abstract: Qualitative Rational Reasoning with Finite Conditional Knowledge Bases
Theoretical and Implementational Aspects
Author
Christian Eichhorn
Publication date
17-12-2018
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 1/2019
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-018-00569-8

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