Date of Award

11-2023

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Dr. Jorge Fandinno

Abstract

Answer Set Programming is an automated reasoning technology that has become a prime candidate for solving knowledge-intense search and optimization problems. One of the main reasons of its success is the availability of highly effective solvers that can go toe-to-toe with Satisfiability Solvers while dealing with a high-level human understandable language. Epistemic logic programs are an extension of Answer Set Programming with subjective literals that allow to succinctly represent several problems that cannot be represented using the standard language of Answer Set Programming. eclingo is a solver developed to solve problems described in the language of Epistemic Logic Programs. This research aims to enhance the efficiency of such solver. The focus of the research will be aimed at the use of the metaprogramming capabilities of Answer Set Programming solver clingo. This will allow us to enhance the solver with new inference rules expressed in the Answer Set Programming language. This will reduce the search space and, in principle, improve solver performance.

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