Translating First-Order Causal Theories Into Answer Set Programming

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 the authors generalize these embeddings to first-order causal logical system that has been used to simplify the semantics of variables in action descriptions.