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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
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Book ChapterDOI
01 Jan 2014
TL;DR: A noble and refined model for abduction inference is proposed and its validity is shown by applying to the inferential process of “Galileo’s discovery of the moons of Jupiter”, with historically considered evidence.
Abstract: The objective of this study is to understand the scientific inferential processes of Galileo’s discovery of Jupiter’s moons. Abductive reasoning has played very important roles in producing creative leaps and breakthrough for scientific discovery in history of science. This article presents a scientific procedure that involves abductive inference in general. And we propose a noble and refined model for abduction inference and show its validity by applying to the inferential process of “Galileo’s discovery of the moons of Jupiter”, with historically considered evidence. It makes three broad macro perspectives; rather than only hypothetico-deductive method, (1) “fixed stars hypothesis suspected”, (2) Moon hypothesis can be suggested and selected by abductive strategies, (3) Moon hypothesis expansion.

2 citations

Journal Article
TL;DR: It was found that Kepler's problem finding in his retinal image theory came from the critical analysis of contemporary theories of vision, based on his relevant knowledge of optics, as he formulated his own hypothesis to build a new theory in eye vision employing optical phenomenon in spherical lens.
Abstract: The aims of this study are to investigate how Kepler found a scientific problem for the retinal image theory and how abductive reasoning was used in his theory development, and to find implications for teaching creativity in science class from his thinking processes in the scientific discovery. Through the analysis of the related literatures, it was found that Kepler's problem finding in his retinal image theory came from the critical analysis of contemporary theories of vision, based on his relevant knowledge of optics, as he formulated his own hypothesis to build a new theory in eye vision employing optical phenomenon in spherical lens, which is a kind of abductive reasoning. From the results, three suggestions are proposed, that: (a) in the development of creativity teaching material, the situations like Kepler's problem finding need to be included in the programs; (b) it should be taught that relevant scientific knowledge is important for problem finding and hypothesis formulating; and (c) the experience of successful problem solving by themselves could help them find new scientific problem(s).

2 citations

Proceedings ArticleDOI
08 Sep 2014
TL;DR: It is shown how deductive and abductive reasoning in distributed authorisation can be efficiently ported to Android.
Abstract: In this paper we show how deductive and abductive reasoning in distributed authorisation can be efficiently ported to Android. Such logical-inference processes prove to be important tools due to the intrinsic autonomic-nature of these mobile devices. Both deduction and abduction are represented by using Constraint Handling Rules (CHR), a high-level declarative constraint programming-language, and implemented in JCHR (CHR embedded into Java). To represent credentials we elaborate on RTW, a weighted Role-based Trust-management family of languages: CHR programs are developed after such languages. In general, having weights associated with credentials leads to a more informative reasoning, for instance, access can be granted only if the total uncertainty is less than 20%.

2 citations

Journal ArticleDOI
20 Dec 2017
TL;DR: The way in which holons handle the unexpected situations can be a model in project management in complex adaptive systems is considered.
Abstract: Risk assessment is one the key activities of any project. The unexpected situations can have catastrophic consequences. Risk assessment tries to estimate to potential known unknowns, but there is no guarantee to foresee all circumstances around a project. In this situation the project team must be adaptive and find solutions by cooperation, creativity and abductive reasoning. In the paper we tried to analyse on what extent a project and a project team can be handled as a complex adaptive system. More precisely, how the scientific and practical achievements of the theory of complex adaptive systems (CAS) can be used in project management. More exactly, we analyse the applicability of the Holonic Multi-Agent Systems in risk management of the projects. We consider the way in which holons handle the unexpected situations can be a model in project management.

2 citations

Proceedings ArticleDOI
24 Oct 2020
TL;DR: In this paper, the authors explore abductive reasoning and context modeling in human-robot interaction and propose a case study, analyzing whether such a system could manage correctly these linguistic phenomena, and further models are proposed to work around the limitations of the case study.
Abstract: Context-dependent meaning recognition in natural language utterances is one of the key problems of computational pragmatics. Abductive reasoning seems apt for modeling and understanding these phenomena. In fact, it presents observations through hypotheses, allowing us to understand subtexts and implied meanings without exact deductions. For this reason in this paper, we are going to explore abductive reasoning and context modeling in human-robot interaction. Rather than a radical inferential approach, we assumed a conventional approach towards context-depending meanings, i.e, they are conventionally encoded rather than inferred from the utterances. In order to address the problem, a case study is presented, analyzing whether such a system could manage correctly these linguistic phenomena. The results obtained confirm the validity of a conventional approach in context modeling and, on this basis, further models are proposed to work around the limitations of the case study.

2 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202356
2022103
202156
202059
201956
201867