A first-order conditional logic for prototypical properties
Artificial Intelligence
A semantical approach to nonmonotonic logics
Readings in nonmonotonic reasoning
An approach to default reasoning based on a first-order conditional logic: revised report
Artificial Intelligence
Probabilistic semantics for nonmonotonic reasoning: a survey
Readings in uncertain reasoning
An introduction to possibilistic and fuzzy logics
Readings in uncertain reasoning
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
An analysis of first-order logics of probability
Artificial Intelligence
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Artificial Intelligence - Special issue on knowledge representation
Conditional logics of normality: a modal approach
Artificial Intelligence
Decidability and expressiveness for first-order logics of probability
Information and Computation
From statistical knowledge bases to degrees of belief
Artificial Intelligence
A two-stage approach to first order default reasoning
Fundamenta Informaticae - Special issue: to the memory of Prof. Helena Rasiowa
Modeling belief in dynamic systems, part I: foundations
Artificial Intelligence
Default Reasoning: Causal and Conditional Theories
Default Reasoning: Causal and Conditional Theories
A Maximum Entropy Approach to Nonmonotonic Reasoning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Preferential Logics: the Predicate Calculus Case
Proceedings of the 3rd Conference on Theoretical Aspects of Reasoning about Knowledge
Plausibility measures and default reasoning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Irrelevance and conditioning in first-order probabilistic logic
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Plausibility measures and default reasoning
Journal of the ACM (JACM)
Analytic tableaux calculi for KLM logics of nonmonotonic reasoning
ACM Transactions on Computational Logic (TOCL)
Automated Deduction for Logics of Default Reasoning
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
From qualitative to quantitative proofs of security properties using first-order conditional logic
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Plausibility measures: a general approach for representing uncertainty
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Conditional and Preferential Logics: Proof Methods and Theorem Proving
Proceedings of the 2010 conference on Conditional and Preferential Logics: Proof Methods and Theorem Proving
Analytic tableau calculi for KLM rational logic R
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
Analytic tableaux for KLM preferential and cumulative logics
LPAR'05 Proceedings of the 12th international conference on Logic for Programming, Artificial Intelligence, and Reasoning
Automating quantified conditional logics in HOL
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Knowledge-Based Policy Conflict Analysis in Mobile Social Networks
Wireless Personal Communications: An International Journal
From Qualitative to Quantitative Proofs of Security Properties Using First-Order Conditional Logic
LICS '13 Proceedings of the 2013 28th Annual ACM/IEEE Symposium on Logic in Computer Science
Hi-index | 0.00 |
Conditional logics play an important role in recent attempts to formulate theories of default reasoning. This paper investigates first-order conditional logic. We show that, as for first-order probabilistic logic, it is important not to confound statistical conditionals over the domain (such as “most birds fly”), and subjective conditionals over possible worlds (such as “I believe that Tweety is unlikely to fly”). We then address the issue of ascribing semantics to first-order conditional logic. As in the propositional case, there are many possible semantics. To study the problem in a coherent way, we use plausibility structures. These provide us with a general framework in which many of the standard approaches can be embedded. We show that while these standard approaches are all the same at the propositional level, they are significantly different in the context of a first-order language. Furthermore, we show that plausibilities provide the most natural extension of conditional logic to the first-order case:we provide a sound and complete axiomatization that contains only the KLM properties and standard axioms of first-order modal logic. We show that most of the other approaches have additional properties, which result in an inappropriate treatment of an infinitary version of the lottery paradox.