On the logic of causal explanation
Artificial Intelligence
Causality in commonsense reasoning about actions
Causality in commonsense reasoning about actions
Strongly equivalent logic programs
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Getting to the airport: the oldest planning problem in AI
Logic-based artificial intelligence
Nested expressions in logic programs
Annals of Mathematics and Artificial Intelligence
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Representing the zoo world and the traffic world in the language of the causal calculator
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
A modular action description language
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
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
Answer sets for propositional theories
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
Translating first-order causal theories into answer set programming
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Logic programs with propositional connectives and aggregates
ACM Transactions on Computational Logic (TOCL)
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Nonmonotonic causal logic, invented by McCain and Turner, is a formalism well suited for representing knowledge about actions, and the definite fragment of that formalism has been implemented in the reasoning and planning system called CCalc. A 1997 theorem due to McCain shows howto translate definite causal theories into logic programming under the answer set semantics, and thus opens the possibility of using answer set programming for the implementation of such theories. In this paper we propose a generalization of McCain's theorem that extends it in two directions. First, it is applicable to arbitrary causal theories, not only definite. Second, it covers causal theories of a more general kind, which can describe non-Boolean fluents.