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Fundamentals of Artificial Intelligence pp 171–217Cite as

Methods of automated reasoning

A tutorial

  • Part Two Knowledge Processing
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 232))

Abstract

This chapter introduces into various aspects and methods of the formalization and automation of processes involved in performing inferences. It views automated inferencing as a machine-oriented simulation of human reasoning. In this sense classical deductive methods for first-order logic like resolution and the connection method are introduced as a derived form of natural deduction. The wide range of phenomena known as non-monotonic reasoning is represented by a spectrum of technical approaches ranging from the closed-world assumption for data bases to the various forms of circumscription. Meta-reasoning is treated as a particularly important technique for modeling many significant features of reasoning including self-reference. Various techniques of reasoning about uncertainty are presented that have become particularly important in knowledge-based systems applications. Many other methods and techniques (like reasoning with time involved) could only briefly — if at all — be mentioned.

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Authors and Affiliations

  1. Technische Universität München, Germany

    Wolfgang Bibel

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  1. Wolfgang Bibel
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Wolfgang Bibel Philippe Jorrand

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© 1986 Springer-Verlag Berlin Heidelberg

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Bibel, W. (1986). Methods of automated reasoning. In: Bibel, W., Jorrand, P. (eds) Fundamentals of Artificial Intelligence. Lecture Notes in Computer Science, vol 232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0022683

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  • DOI: https://doi.org/10.1007/BFb0022683

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-16782-2

  • Online ISBN: 978-3-540-39875-2

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