Handbook of logic in artificial intelligence and logic programming (vol. 3)
On the logic of causal explanation
Artificial Intelligence
Causality in commonsense reasoning about actions
Causality in commonsense reasoning about actions
An action language based on causal explanation: preliminary report
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
A library of general-purpose action descriptions
A library of general-purpose action descriptions
A modular action description language
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
The semantics of variables in action descriptions
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
A logic program characterization of causal theories
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A new perspective on stable models
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Symmetric splitting in the general theory of stable models
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Causal theories of action and change
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Coala: a compiler from action languages to ASP
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Stable models and circumscription
Artificial Intelligence
Answer sets for propositional theories
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
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Nonmonotonic causal logic became a basis for the semantics of several expressive action languages. Norman McCain and Paolo Ferraris showed how to embed propositional causal theories into logic programming, and this work paved the way to the use of answer set solvers for answering queries about actions described in causal logic. In this paper we generalize these embeddings to first-order causal logic--a system that has been used to simplify the semantics of variables in action descriptions.