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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Bibel, W. (1987). Methods of Automated Reasoning. In: Bibel, W., Jorrand, P. (eds) Fundamentals of Artificial Intelligence. Springer Study Edition. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-40145-3_5
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DOI: https://doi.org/10.1007/978-3-662-40145-3_5
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