Non-monotonic inference
| Abstract | Non-monotonic inference is inference that is defeasible: in contrast with deductive inference, the conclusions drawn may be withdrawn in the light of further information, even though all the original premises are retained. Much of our everyday reasoning is like this, and a non-monotonic approach has applications to a number of technical problems in artificial intelligence. Work on formalizing non-monotonic inference has progressed rapidly since its beginnings in the 1970s, and a number of mature theories now exist – the most important being default logic, autoepistemic logic, and circumscription. | |||||||||
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G. Aldo Antonelli (1996). Defeasible Reasoning as a Cognitive Model. In Krister Segerberg (ed.), The Parikh Project. Seven Papers in Honour of Rohit. Uppsala Prints & Preprints in Philosophy.
G. Aldo Antonelli (2000). Book Review To Appear in the Bulletin of Symbolic Logic. [REVIEW] Bulletin of Symbolic Logic 6 (4):480-84.
E. G. K. López-Escobar (1988). Circumscription Within Monotonic Inferences. Journal of Symbolic Logic 53 (3):888-904.
Kenneth G. Ferguson (2003). Monotonicity in Practical Reasoning. Argumentation 17 (3):335-346.
Diderik Batens (2001). A Dynamic Characterization of the Pure Logic of Relevant Implication. Journal of Philosophical Logic 30 (3):267-280.
Jan-R. Sieckmann (2003). Why Non-Monotonic Logic is Inadequate to Represent Balancing Arguments. Artificial Intelligence and Law 11 (2-3):211-219.
Gregory Wheeler (2008). Applied Logic Without Psychologism. Studia Logica 88 (1):137 - 156.
James Hawthorne (1988). A Semantic Approach to Non-Monotonic Conditionals. In J. F. Lemmer & L. N. Kanal (eds.), Uncertainty in Artificial Intelligence 2. Elsevier.
G. Aldo Antonelli, Non-Monotonic Logic. Stanford Encyclopedia of Philosophy.
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