Defeasible Reasoning

doi:10.1017/CBO9780511814273.025

23 - Defeasible Reasoning

Published online by Cambridge University Press: 05 June 2012

John L. Pollock

Edited by

Jonathan E. Adler and

Lance J. Rips

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John L. Pollock: Affiliation:
University of Arizona
Jonathan E. Adler: Affiliation:
Brooklyn College, City University of New York
Lance J. Rips: Affiliation:
Northwestern University, Illinois

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Summary

The Inadequacy of Deductive Reasoning

There was a long tradition in philosophy according to which good reasoning had to be deductively valid. However, that tradition began to be questioned in the 1960s, and is now thoroughly discredited. What caused its downfall was the recognition that many familiar kinds of reasoning are not deductively valid, but clearly confer justification on their conclusions. Here are some simple examples:

PERCEPTION

Most of our knowledge of the world derives from some form of perception. But clearly, perception is fallible. For instance, I may believe that the wall is gray on the basis of its looking gray to me. But it may actually be white, and it only looks gray because it is dimly illuminated. In this example, my evidence (the wall's looking gray) makes it reasonable for me to conclude that the wall is gray, but further evidence could force me to retract that conclusion. Such a conclusion is said to be justified defeasibly, and the considerations that would make it unjustified are defeaters.

INDUCTION

There is one kind of reasoning that few ever supposed to be deductive, but it was often conveniently ignored when claiming that good reasoning had to be deductive. This is inductive reasoning, where we generalize from a restricted sample to an unrestrictedly general conclusion. For example, having observed a number of mammals and noted that they were all warm-blooded, biologists concluded that all mammals are warm-blooded. Hume's concern with induction was just that it is not deductive.

Type: Chapter
Information: Reasoning
Studies of Human Inference and its Foundations
, pp. 451 - 470

DOI: https://doi.org/10.1017/CBO9780511814273.025 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2008

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References

Chisholm, Roderick 1957 Perceiving. Ithaca, NY: Cornell University Press.Google Scholar

Chisholm, Roderick 1966 Theory of Knowledge, Englewood Cliffs, NJ: PrenticeHall.Google Scholar

Fodor, Jerry 2001 The Mind Doesn't Work That Way, Cambridge, MA: MIT Press.Google Scholar

Gelfond, Michael, and Lifschitz, Vladimir 1993 “Representing action and change by logic programs,” Journal of Logic Programming 17, 301–322.CrossRef Google Scholar

Ginsberg, Matt 1987 Readings in Nonmonotonic Reasoning. Los Altos, CA: Morgan Kaufman.Google Scholar

Hanks, Steve, and McDermott, Drew 1987 ”Nonmonotonic logic and temporal projection,” Artificial Intelligence, 33, 379–412CrossRef Google Scholar

Harman, Gilbert 1973 Thought. Princeton, NJ: Princeton University Press.Google Scholar

Hart, H. L. A. 1948 “The ascription of responsibility and rights,” Proceedings of the Aristotelian Society, 1948–9.Google Scholar

Israel, David 1980 “What's wrong with non-monotonic logic?” Proceedings of the First Annual National Conference on Artificial Intelligence, 99–101.Google Scholar

Kyburg, Henry, Jr. 1961 Probability and the Logic of Rational Belief. Middletown, CT: Wesleyan University Press.Google Scholar

Kyburg, Henry, Jr. 1970 “Conjunctivitis,” Swain, Marshall (ed.), Induction, Accveptance, and Rational Belief. Dordrecht, D. Reidel.Google Scholar

Lin, Fangzhen, and Reiter, Raymond 1994 “How to progress a database (and why) I. Logical foundations.” In Proceedings of the Fourth International Conference on Principles of Knowledge Representation (KR'94). 425–436.Google Scholar

Lin, Fangzhen, and Reiter, Raymond 1995 “How to progress a database II: The STRIPS connection.” IJCAI-95. 2001–2007.Google Scholar

Makinson, D., and Schlechta, K. 1991 “Floating conclusions and zombie paths: Two deep difficulties in the ‘directly skeptical’ approach to inheritance nets” Artificial Intelligence 48, 199–209.CrossRef Google Scholar

McCarthy, John 1980 “Circumscription – A form of non-monotonic reasoning,” Artificial Intelligence 13, 27–39, 171–172.CrossRef Google Scholar

McCarthy, John 1986 “Applications of circumscription to formalizing common sense knowledge.” Artificial Intelligence 26, 89–116.CrossRef Google Scholar

McCarthy, John, and Hayes, Patrick 1969 “Some philosophical problems from the standpoint of artificial intelligence.” In Metzer, B. & Michie, D. (eds.), Machine Intelligence 4. Edinburgh: Edinburgh University Press.Google Scholar

McDermott, Drew 1982 “A temporal logic for reasoning about processes and plans,” Cognitive Science 6, 101–155.CrossRef Google Scholar

McDermott, D., and Doyle, Jon 1980 “Non-monotonic logic I,” Artificial Intelligence 13: 41–72.CrossRef Google Scholar

Pollock, John 1967 “Criteria and our knowledge of the material world,” The Philosophical Review, 76, 28–60.CrossRef Google Scholar

Pollock, John 1970 “The structure of epistemic justification,” American Philosophical Quarterly, monograph series 4: 62–78.Google Scholar

Pollock, John 1971 “Perceptual knowledge,” Philosophical Review, 80, 287–319.CrossRef Google Scholar

Pollock, John 1974 Knowledge and Justification, Princeton University Press.Google Scholar

Pollock, John 1979 Subjunctive Reasoning, D. Reidel.Google Scholar

Pollock, John 1984 The Foundations of Philosophical Semantics, Princeton University Press.Google Scholar

Pollock, John 1986 Contemporary Theories of Knowledge, Rowman and Littlefield.Google Scholar

Pollock, John 1990 Nomic Probability and the Foundations of Induction, Oxford University Press.Google Scholar

Pollock, John 1991 “Self-defeating arguments,” Minds and Machines 1, 367–392.CrossRef Google Scholar

Pollock, John 1995 Cognitive Carpentry, MIT Press.Google Scholar

Pollock, John 1997 “Reasoning about change and persistence: a solution to the frame problem,” Nous 31, 143–169.CrossRef Google Scholar

Pollock, John 1998 “Perceiving and reasoning about a changing world,” Computational Intelligence, 14, 498–562.CrossRef Google Scholar

Pollock, John 2002 “Defeasible reasoning with variable degrees of justification,” Artificial Intelligence 133, 233–282.CrossRef Google Scholar

Pollock, John 2006 Thinking about Acting: Logical Foundations for Rational Decision Making. New York, Oxford.CrossRef Google Scholar

Pollock, John and Oved, Iris 2006 “Vision, knowledge, and the mystery link.” In Philosophical Perspectives 19.Google Scholar

Reiter, Raymond 1980 “A logic for default reasoning,” Artificial Intelligence 13, 81–132.CrossRef Google Scholar

Rescher, Nicholas 1977 Dialectics, Albany: SUNY Albany Press.Google Scholar

Sandewall, Erik 1972 “An approach to the frame problem and its implementation.” In Metzer, B. and Michie, D. (eds.), Machine Intelligence 7. Edinburgh: Edinburgh University Press.Google Scholar

Shoham, Yoav 1987 Reasoning about Change. Cambridge, MA: MIT Press.Google Scholar

Stalker, Douglas 1994 Grue: The New Riddle of Induction. Chicago: Open Court.Google Scholar

Toulmin, Stephen 1958 The Place of Reason in Ethics, Cambridge, MA: MIT Press.Google Scholar