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Abductive reasoning

Abductive reasoning (also called abduction,[1] abductive inference,[1] or retroduction[2]) is a form of logical inference that seeks the simplest and most likely conclusion from a set of observations. It was formulated and advanced by American philosopher and logician Charles Sanders Peirce beginning in the latter half of the 19th century.

"Abductive" redirects here. For other uses, see Abduction (disambiguation).

Abductive reasoning, unlike deductive reasoning, yields a plausible conclusion but does not definitively verify it. Abductive conclusions do not eliminate uncertainty or doubt, which is expressed in retreat terms such as "best available" or "most likely". While inductive reasoning draws general conclusions that apply to many situations, abductive conclusions are confined to the particular observations in question.


In the 1990s, as computing power grew, the fields of law,[3] computer science, and artificial intelligence research[4] spurred renewed interest in the subject of abduction.[5] Diagnostic expert systems frequently employ abduction.[6]

Formalizations of abduction[edit]

Logic-based abduction[edit]

In logic, explanation is accomplished through the use of a logical theory representing a domain and a set of observations . Abduction is the process of deriving a set of explanations of according to and picking out one of those explanations. For to be an explanation of according to , it should satisfy two conditions:

Abduction is guessing. It is "very little hampered" by rules of logic.[20] Even a well-prepared mind's individual guesses are more frequently wrong than right.[21] But the success of our guesses far exceeds that of random luck and seems born of attunement to nature by instinct[22] (some speak of intuition in such contexts[23]).

[19]

Abduction guesses a new or outside idea so as to account in a plausible, instinctive, economical way for a surprising or very complicated phenomenon. That is its proximate aim.

[22]

Its longer aim is to economize itself. Its rationale is inductive: it works often enough, is the only source of new ideas, and has no substitute in expediting the discovery of new truths.[24] Its rationale especially involves its role in coordination with other modes of inference in inquiry. It is inference to explanatory hypotheses for selection of those best worth trying.

inquiry

is the logic of abduction. Upon the generation of an explanation (which he came to regard as instinctively guided), the pragmatic maxim gives the necessary and sufficient logical rule to abduction in general. The hypothesis, being insecure, needs to have conceivable[25] implications for informed practice, so as to be testable[26][27] and, through its trials, to expedite and economize inquiry. The economy of research is what calls for abduction and governs its art.[28]

Pragmatism

Applications[edit]

Artificial intelligence[edit]

Applications in artificial intelligence include fault diagnosis, belief revision, and automated planning. The most direct application of abduction is that of automatically detecting faults in systems: given a theory relating faults with their effects and a set of observed effects, abduction can be used to derive sets of faults that are likely to be the cause of the problem.[4]

Medicine[edit]

In medicine, abduction can be seen as a component of clinical evaluation and judgment.[54][55]

Automated planning[edit]

Abduction can also be used to model automated planning.[56] Given a logical theory relating action occurrences with their effects (for example, a formula of the event calculus), the problem of finding a plan for reaching a state can be modeled as the problem of abducting a set of literals implying that the final state is the goal state.

Intelligence analysis[edit]

In intelligence analysis, analysis of competing hypotheses and Bayesian networks, probabilistic abductive reasoning is used extensively. Similarly in medical diagnosis and legal reasoning, the same methods are being used, although there have been many examples of errors, especially caused by the base rate fallacy and the prosecutor's fallacy.

Douven, Igor. . In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy.

"Abduction"

at the Indiana Philosophy Ontology Project

Abductive reasoning

at PhilPapers

Abductive reasoning

"" (once there, scroll down), John R. Josephson, Laboratory for Artificial Intelligence Research, Ohio State University. (Former webpage via the Wayback Machine.)

Abductive Inference

"", Chapter 3 in article "Charles Sanders Peirce" by Robert W. Burch, 2001 and 2006, in the Stanford Encyclopedia of Philosophy.

Deduction, Induction, and Abduction

"", links to articles and websites on abductive inference, Martin Ryder.

Abduction

Uwe Wirth and Alexander Roesler, eds. Uses frames. Click on link at bottom of its home page for English. Wirth moved to U. of Gießen, Germany, and set up Abduktionsforschung, home page not in English but see Artikel section there. Abduktionsforschung home page via Google translation.

International Research Group on Abductive Inference

"" (1981), by Thomas Sebeok with Jean Umiker-Sebeok, from The Play of Musement, Thomas Sebeok, Bloomington, Indiana: Indiana University Press, pp. 17–52.

'You Know My Method': A Juxtaposition of Charles S. Peirce and Sherlock Holmes

Mats Bergman and Sami Paavola, editors, Helsinki U. Peirce's own definitions, often many per term across the decades. There, see "Hypothesis [as a form of reasoning]", "Abduction", "Retroduction", and "Presumption [as a form of reasoning]".

Commens Dictionary of Peirce's Terms

a critique of abductive reasoning in the context of cosmology.

"Touching Reality"