Tools and Methodologies for Verifying Answer Set Programs

TL;DR

This paper discusses the development of tools and methodologies to verify answer set programs, enhancing their reliability, explainability, and trustworthiness in AI applications.

Contribution

It introduces new verification techniques and tools that improve the formal analysis and correctness assurance of ASP programs.

Findings

Enhanced verification methods for ASP programs

Improved formal analysis tools for ASP

Contributions towards trustworthy AI with ASP

Abstract

Answer Set Programming (ASP) is a powerful declarative programming paradigm commonly used for solving challenging search and optimization problems. The modeling languages of ASP are supported by sophisticated solving algorithms (solvers) that make the solution search efficient while enabling the programmer to model the problem at a high level of abstraction. As an approach to Knowledge Representation and Reasoning, ASP benefits from its simplicity, conciseness and rigorously defined semantics. These characteristics make ASP a straightforward way to develop formally verifiable programs. In the context of artificial intelligence (AI), the clarity of ASP programs lends itself to the construction of explainable, trustworthy AI. In support of these goals, my research is concerned with extending the theory and tools supporting the verification of ASP progams.