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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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Journal ArticleDOI
T. Givón1
TL;DR: The history of the treatment of both semantics and pragmatics in Linguistics has been until recently a captive of over-logicization, where the deductive, algorithmic, close-ended, context-free properties of the system were over-emphasized to the detriment of a more realistic view of facts of natural language as discussed by the authors.

70 citations

Book
02 May 2012
TL;DR: In this article, the authors present a survey of abduction as a means of conceptualizing processes of discovery in philosophy of science and argue that it is useful to distinguish between IBE (Harmanian abduction) and Hansonian abduction.
Abstract: The purpose of this study was to analyze and develop various forms of abduction as a means of conceptualizing processes of discovery. Abduction was originally presented by Charles S. Peirce (1839-1914) as a “weak”, third main mode of inference -besides deduction and induction -one which, he proposed, is closely related to many kinds of cognitive processes, such as instincts, perception, practices and mediated activity in general. Both abduction and discovery are controversial issues in philosophy of science. It is often claimed that discovery cannot be a proper subject area for conceptual analysis and, accordingly, abduction cannot serve as a “logic of discovery”. I argue, however, that abduction gives essential means for understanding processes of discovery although it cannot give rise to a manual or algorithm for making discoveries. In the first part of the study, I briefly present how the main trend in philosophy of science has, for a long time, been critical towards a systematic account of discovery. Various models have been suggested. I outline a short history of abduction; first Peirce's evolving forms of his theory, and then later developments. Although abduction has not been a major area of research until quite recently, I review some critiques of it and look at the ways it has been analyzed, developed and used in various fields of research. Peirce’s own writings and later developments, I argue, leave room for various subsequent interpretations of abduction. The second part of the study consists of six research articles. First I treat “classical” arguments against abduction as a logic of discovery. I show that by developing strategic aspects of abductive inference these arguments can be countered. Nowadays the term ‘abduction’ is often used as a synonym for the Inference to the Best Explanation (IBE) model. I argue, however, that it is useful to distinguish between IBE (“Harmanian abduction”) and “Hansonian abduction”; the latter concentrating on analyzing processes of discovery. The distinctions between loveliness and likeliness, and between potential and actual explanations are more fruitful within Hansonian abduction. I clarify the nature of abduction by using Peirce’s distinction between three areas of “semeiotic”: grammar, critic, and methodeutic. Grammar (emphasizing “Firstnesses” and iconicity) and methodeutic (i.e., a processual approach) especially, give new means for understanding abduction. Peirce himself held a controversial view that new abductive ideas are products of an instinct and an inference at the same time. I maintain that it is beneficial to make a clear distinction between abductive inference and abductive instinct, on the basis of which both can be developed further. Besides these, I analyze abduction as a part of distributed cognition which emphasizes a long-term interaction with the material, social and cultural environment as a source for abductive ideas. This approach suggests a “trialogical” model in which inquirers are fundamentally connected both to other inquirers and to the objects of inquiry. As for the classical Meno paradox about discovery, I show that abduction provides more than one answer. As my main example of abductive methodology, I analyze the process of Ignaz Semmelweis’ research on childbed fever. A central basis for abduction is the claim that discovery is not a sequence of events governed only by processes of chance. Abduction treats those processes which both constrain and instigate the search for new ideas; starting from the use of clues as a starting point for discovery, but continuing in considerations like elegance and 'loveliness'. The study then continues a PeirceanHansonian research programme by developing abduction as a way of analyzing processes of discovery.

69 citations

Journal ArticleDOI
TL;DR: This work addresses the computational complexity of why a given tuple is missing in a query answer for arbitrary, subset minimal, and cardinality minimal explanations by adopting abductive reasoning.
Abstract: In order to meet usability requirements, most logic-based applications provide explanation facilities for reasoning services. This holds also for Description Logics, where research has focused on the explanation of both TBox reasoning and, more recently, query answering. Besides explaining the presence of a tuple in a query answer, it is important to explain also why a given tuple is missing. We address the latter problem for instance and conjunctive query answering over DL-Lite ontologies by adopting abductive reasoning; that is, we look for additions to the ABox that force a given tuple to be in the result. As reasoning tasks we consider existence and recognition of an explanation, and relevance and necessity of a given assertion for an explanation. We characterize the computational complexity of these problems for arbitrary, subset minimal, and cardinality minimal explanations.

68 citations

01 Jan 1988

67 citations

Journal ArticleDOI
TL;DR: Abduction not only classifies the distinct type of reasoning performed when neural networks are applied, but gives a logical framework for expanding current neural network research to include network concepts not constrained by neuron analogies.

67 citations


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