FO(C): A Knowledge Representation Language of Causality
This work addresses the problem of representing complex causal relations in knowledge representation, which is incremental as it builds on existing formalisms.
The paper tackles the limited expressiveness of existing formalisms for representing causal knowledge by introducing FO(C), a new language that integrates C-Log with first-order logic to allow more expressive specifications of effects, such as object creation. It compares FO(C) with related languages like inductive definitions and Datalog extensions.
Cause-effect relations are an important part of human knowledge. In real life, humans often reason about complex causes linked to complex effects. By comparison, existing formalisms for representing knowledge about causal relations are quite limited in the kind of specifications of causes and effects they allow. In this paper, we present the new language C-Log, which offers a significantly more expressive representation of effects, including such features as the creation of new objects. We show how C-Log integrates with first-order logic, resulting in the language FO(C). We also compare FO(C) with several related languages and paradigms, including inductive definitions, disjunctive logic programming, business rules and extensions of Datalog.