Modeling and Reasoning in Event Calculus using Goal-Directed Constraint Answer Set Programming

Automated commonsense reasoning is essential for building human-like AI\nsystems featuring, for example, explainable AI. Event Calculus (EC) is a family\nof formalisms that model commonsense reasoning with a sound, logical basis.\nPrevious attempts to mechanize reasoning using EC faced difficulties in the\ntreatment of the continuous change in dense domains (e.g., time and other\nphysical quantities), constraints among variables, default negation, and the\nuniform application of different inference methods, among others. We propose\nthe use of s(CASP), a query-driven, top-down execution model for Predicate\nAnswer Set Programming with Constraints, to model and reason using EC. We show\nhow EC scenarios can be naturally and directly encoded in s(CASP) and how it\nenables deductive and abductive reasoning tasks in domains featuring\nconstraints involving both dense time and dense fluents.\n