scispace - formally typeset
Search or ask a question
Topic

Abductive reasoning

About: Abductive reasoning is a research topic. Over the lifetime, 1917 publications have been published within this topic receiving 44645 citations. The topic is also known as: abduction & abductive inference.


Papers
More filters
Proceedings ArticleDOI
28 Aug 2014
TL;DR: An approach composed by two different procedures, both relying on OWL-DL and SWRL Rules, in order to generate policy explanations, which makes use of OWL Explanation and abductive reasoning.
Abstract: Providing reliable explanations for the causes of an access response represents an important improvement of applications usability and effectiveness, in a context where users are permitted or denied access to resources. I present an approach composed by two different procedures, both relying on OWL-DL and SWRL Rules, in order to generate policy explanations. The first procedure makes use of OWL Explanation and abductive reasoning. The second uses an algorithm of Association Rule Learning to identifying attributes and states arising together with policy privileges, in an inductive way. The PosSecCo IT Policy language is used in the present paper for representing the policies, but the approach is general enough to be applied in other environments as well.

4 citations

Posted Content
TL;DR: This paper discusses the relation between modeling, and in particular abstraction in the model, and the notion of diagnosis, and finds the right way of abstracting the behavior of the system to be modeled.
Abstract: Diagnostic reasoning has been characterized logically as consistency-based reasoning or abductive reasoning. Previous analyses in the literature have shown, on the one hand, that choosing the (in general more restrictive) abductive definition may be appropriate or not, depending on the content of the knowledge base [Console&Torasso91], and, on the other hand, that, depending on the choice of the definition the same knowledge should be expressed in different form [Poole94]. Since in Model-Based Diagnosis a major problem is finding the right way of abstracting the behavior of the system to be modeled, this paper discusses the relation between modeling, and in particular abstraction in the model, and the notion of diagnosis.

4 citations

Proceedings ArticleDOI
08 Nov 1993
TL;DR: The authors have implemented a system to make abductive reasoning to clarify hidden information and resolve the problem of noun phrase reference.
Abstract: The authors developed a language QUIXOTE as a tool to deal with various information in natural language processing. QUIXOTE is a hybrid language of a deductive object-oriented database and constraint logic programming language. The new mechanism of QUIXOTE is a combination of an object-orientation concept such as object identity and the concept of a module that classifies a large knowledge base. In addition, its logical inference system is extended to be able to make restricted abduction. The authors first apply QUIXOTE to the sorted feature structure of constraint-based grammar formalisms. Next, it is shown that QUIXOTE can contribute to the description of situation-based semantics. The authors have implemented a system to make abductive reasoning to clarify hidden information. Also, they resolve the problem of noun phrase reference.

4 citations

Posted Content
TL;DR: A new approach for calculating the root cause for an observed failure in an IT infrastructure, based on Abduction in Markov Logic Networks, which exhibits a high amount of reusability and enables users without specific knowledge of a concrete infrastructure to gain viable insights in the case of an incident.
Abstract: IT infrastructure is a crucial part in most of today's business operations. High availability and reliability, and short response times to outages are essential. Thus a high amount of tool support and automation in risk management is desirable to decrease outages. We propose a new approach for calculating the root cause for an observed failure in an IT infrastructure. Our approach is based on Abduction in Markov Logic Networks. Abduction aims to find an explanation for a given observation in the light of some background knowledge. In failure diagnosis, the explanation corresponds to the root cause, the observation to the failure of a component, and the background knowledge to the dependency graph extended by potential risks. We apply a method to extend a Markov Logic Network in order to conduct abductive reasoning, which is not naturally supported in this formalism. Our approach exhibits a high amount of reusability and enables users without specific knowledge of a concrete infrastructure to gain viable insights in the case of an incident. We implemented the method in a tool and illustrate its suitability for root cause analysis by applying it to a sample scenario.

4 citations

01 Jan 1995
TL;DR: This paper presents a formal sphere semantics for abductive expansion, a method for selecting those worlds consistent with the abductively expanded epistemic state by imposing an ordering over the possible worlds that are consistent with current beliefs, and investigates an epistemic entrenchment style ordering over formulae.
Abstract: When dealing with a situation in which new information is to be incorporated into an epistemic state, most belief revision frameworks, including the AGM, incorporate solely this new information. A more natural proposal is that the agent seeks some explanation or justification first and attempts to incorporate the new information together with its justification into the agent’s current epistemic state. Pagnucco, Nayak and Foo model this proposal by developing a belief change operator known as abductive expansion which adds abductive inference to the belief expansion process. They develop rationality postulates for abductive belief expansion and provide a construction in terms of selection functions. However, this account lacks a proper semantic treatment. In this paper we present a formal sphere semantics for abductive expansion. By imposing an ordering over the possible worlds that are consistent with current beliefs we demonstrate a method for selecting those worlds consistent with the abductively expanded epistemic state. We also investigate an epistemic entrenchment style ordering over formulae which can be used to determine those formulae to be incorporated into the new epistemic state. This ordering has important consequences for expectation orderings and nonmonotonic inference. Using observations first made by Gardenfors & Makinson and Williams we indicate how this entrenchment may be used for default reasoning. We also translate the abductive expansion postulates into conditions on a nonmonotonic consequence relation j .

4 citations


Network Information
Related Topics (5)
Natural language
31.1K papers, 806.8K citations
82% related
Ontology (information science)
57K papers, 869.1K citations
79% related
Inference
36.8K papers, 1.3M citations
76% related
Heuristics
32.1K papers, 956.5K citations
76% related
Social network
42.9K papers, 1.5M citations
75% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202356
2022103
202156
202059
201956
201867