Abstract
Nonmonotonic inference systems, i.e., inference systems that fail to satisfy the monotonicity principle (c2), arose as a result of the search for logical tools which can handle a variety of forms of reasoning involving inferences based on information which can be incomplete, uncertain, approximate, or subject to revision. In this chapter we show one possible way of extending the resolution proof system methodology developed in the previous chapters to cumulative nonmonotonic inference systems.
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© 1996 Kluwer Academic Publishers
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Stachniak, Z. (1996). Nonmonotonic Resolution Inference Systems. In: Resolution Proof Systems. Automated Reasoning Series, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-1677-7_8
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DOI: https://doi.org/10.1007/978-94-009-1677-7_8
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-7251-9
Online ISBN: 978-94-009-1677-7
eBook Packages: Springer Book Archive