Abductive Reasoning

Abductive Reasoning

Abduction is a form of logical inference that goes from data description of something to a hypothesis that accounts for the reliable data and seeks to explain relevant evidence. The term was first introduced by the American philosopher Charles Sanders Peirce (1839–1914) as "guessing". Peirce said that to abduce a hypothetical explanation from an observed surprising circumstance is to surmise that may be true because then would be a matter of course. Thus, to abduce from involves determining that is sufficient (or nearly sufficient), but not necessary, for .

For example, the lawn is wet. But if it rained last night, then it would be unsurprising that the lawn is wet. Therefore, by abductive reasoning, the possibility that it rained last night is reasonable. (But note that Peirce did not remain convinced that a single logical form covers all abduction.)

Peirce argues that good abductive reasoning from P to Q involves not simply a determination that, e.g., Q is sufficient for P, but also that Q is among the most economical explanations for P. Simplification and economy are what call for the 'leap' of abduction.

In abductive reasoning, unlike in deductive reasoning, the premises do not guarantee the conclusion. Abductive reasoning can be understood as "inference to the best explanation".

There has been renewed interest in the subject of abduction in the fields of law, computer science, and artificial intelligence research.