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The Case for Psychologism in Default and Inheritance Reasoning

Francis Jeffry Pelletier and Renée Elio
Synthese
Vol. 146, No. 1/2, Non-Monotonic and Uncertain Reasoning in Cognition (Aug., 2005), pp. 7-35
Published by: Springer
Stable URL: http://www.jstor.org/stable/20118614
Page Count: 29
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The Case for Psychologism in Default and Inheritance Reasoning
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Abstract

Default reasoning occurs whenever the truth of the evidence available to the reasoner does not guarantee the truth of the conclusion being drawn. Despite this, one is entitled to draw the conclusion "by default" on the grounds that we have no information which would make us doubt that the inference should be drawn. It is the type of conclusion we draw in the ordinary world and ordinary situations in which we find ourselves. Formally speaking, 'nonmonotonic reasoning' refers to argumentation in which one uses certain information to reach a conclusion, but where it is possible that adding some further information to those very same premises could make one want to retract the original conclusion. It is easily seen that the informal notion of default reasoning manifests a type of nonmonotonic reasoning. Generally speaking, default statements are said to be true about the class of objects they describe, despite the acknowledged existence of "exceptional instances" of the class. In the absence of explicit information that an object is one of the exceptions we are enjoined to apply the default statement to the object. But further information may later tell us that the object is in fact one of the exceptions. So this is one of the points where nonmonotonicity resides in default reasoning. The informal notion has been seen as central to a number of areas of scholarly investigation, and we canvass some of them before turning our attention to its role in AI. It is because ordinary people so cleverly and effortlessly use default reasoning to solve interesting cognitive tasks that nonmonotonic formalisms were introduced into AI, and we argue that this is a form of psychologism, despite the fact that it is not usually recognized as such in AI. We close by mentioning some of the results from our empirical investigations that we believe should be incorporated into nonmonotonic formalisms.

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