Semantical considerations on nonmonotonic logic
Artificial Intelligence
Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
The mathematics of inheritance systems
The mathematics of inheritance systems
Nonmonotonic logic and temporal projection
Artificial Intelligence
Reasoning about change: time and causation from the standpoint of artificial intelligence
Reasoning about change: time and causation from the standpoint of artificial intelligence
Reasoning about action I: a possible worlds approach
Artificial Intelligence
Embracing causality in fault reasoning
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Towards a theory of declarative knowledge
Foundations of deductive databases and logic programming
On the declarative semantics of deductive databases and logic programs
Foundations of deductive databases and logic programming
Default reasoning, minimality and coherence
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Default reasoning: causal and conditional theories
Default reasoning: causal and conditional theories
Predicting causality ascriptions from background knowledge: model and experimental validation
International Journal of Approximate Reasoning
Causes and explanations in the structural-model approach
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Structure-based causes and explanations in the independent choice logic
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
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Causal theories are default theories which explicitly accommodate a distinction between 'explained' and 'unexplained' propositions. This is accomplished by means of an operator 'c' in the language for which propositions α are assumed explained when literals of the form Cα hold. The behavior of causal theories is determined by a preference relation on models based on the minimization of unexplained abnormality. We show that causal networks, general logic programs and theories for reasoning about change can be all naturally expressed as causal theories. We also develop a proof-theory for causal theories and discuss how they relate to autoepistemic theories, prioritized circumscription and Pearl's C-E calculus.