General theory of cumulative inference
Proceedings of the 2nd international workshop on Non-monotonic reasoning
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Theoretical foundations for non-monotonic reasoning in expert systems
Logics and models of concurrent systems
What does a conditional knowledge base entail?
Artificial Intelligence
Nonmonotonic inference based on expectations
Artificial Intelligence
General patterns in nonmonotonic reasoning
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Predicting causality ascriptions from background knowledge: model and experimental validation
International Journal of Approximate Reasoning
Background default knowledge and causality ascriptions
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Qualitative and quantitative conditions for the transitivity of perceived causation
Annals of Mathematics and Artificial Intelligence
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Human inference can be used to test the inference patterns a reliable nonmonotonic consequence should satisfy, because it appears to be nonmonotonic, it is adaptive and it generally achieves efficiency. In this study, an experiment is conducted to investigate whether human inference tends to be consistent with rationality postulates (System P plus Rational Monotony), especially when it no longer satisfies the Monotony property. The experimental protocol uses a possibilistic semantics for plausible rules. Our results appear to be consistent with all the studied properties. Exceptions are the Cut property (with one kind of content out of two) and Left Logical Equivalence which could not be tested. Moreover, when Monotony was not satisfied by participants' inferences, Cut, Cautious Monotony and And properties were corroborated (Rational Monotony was only plausibly supported and the other properties were not tested). Our results emphasize the psychological plausibility of rationality postulates and support the working hypothesis in Artificial Intelligence that System P plus Rational Monotony offer a plausible basic set of properties for nonmonotonic logics.