Methods of automated reasoning

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


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.


Natural Deduction Horn Clause Default Rule Default Theory Existential Quantifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1986

Authors and Affiliations

  1. 1.Technische Universität MünchenGermany

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