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

Automated commonsense reasoning (CR) is essential for building human-like AI systems featuring, for example, explainable AI. Event calculus (EC) is a family of formalisms that model CR with a sound, logical basis. Previous attempts to mechanize reasoning using EC faced difficulties in the treatment...

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Bibliographic Details
Published in:Theory and practice of logic programming Vol. 22; no. 1; pp. 51 - 80
Main Authors: ARIAS, JOAQUÍN, CARRO, MANUEL, CHEN, ZHUO, GUPTA, GOPAL
Format: Journal Article
Language:English
Published: Cambridge Cambridge University Press 01.01.2022
Subjects:
Calculus
Constraint modelling
Declarative programming
Logic programming
Mathematical programming
Reasoning
Semantics
Variables
ISSN:1471-0684, 1475-3081
Online Access:Get full text
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Summary:Automated commonsense reasoning (CR) is essential for building human-like AI systems featuring, for example, explainable AI. Event calculus (EC) is a family of formalisms that model CR with a sound, logical basis. Previous attempts to mechanize reasoning using EC faced difficulties in the treatment of the continuous change in dense domains (e.g. time and other physical quantities), constraints among variables, default negation, and the uniform application of different inference methods, among others. We propose the use of s(CASP), a query-driven, top-down execution model for Predicate Answer Set Programming with Constraints, to model and reason using EC. We show how EC scenarios can be naturally and directly encoded in s(CASP) and how it enables deductive and abductive reasoning tasks in domains featuring constraints involving both dense time and dense fluents.
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ISSN:1471-0684
1475-3081
DOI:10.1017/S1471068421000156