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Part of the book series: Artificial Intelligence ((AI))

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Abstract

Taken in a broader perspective, a theory of nonmonotonic reasoning gives us (or, more exactly, should give) a more direct and adequate description of the actual ways we think about the world. More often than not we reason and act in situations where we do not or even cannot have complete information. So, deductive reasoning, taken by itself, simply cannot help us in such situations. Still, we usually need to act in such situations in a reasonable way, and it is here that nonmonotonic reasoning finds its place. This means, in particular, that the necessity of nonmonotonic reasoning does not stem from computational considerations, as is sometimes supposed in Artificial Intelligence; it is not the question of speeding or simplifying our reasoning. Rather, it is a matter of vital necessity: we have to act reasonably in situations of partial knowledge in order to achieve our practical and theoretical goals.

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© 2001 Springer-Verlag Berlin Heidelberg

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Bochman, A. (2001). Introduction. In: A Logical Theory of Nonmonotonic Inference and Belief Change. Artificial Intelligence. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04560-2_1

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  • DOI: https://doi.org/10.1007/978-3-662-04560-2_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-07516-2

  • Online ISBN: 978-3-662-04560-2

  • eBook Packages: Springer Book Archive

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