Extracting Policies from Quantified Answer Set Programs

TL;DR

This paper introduces an algorithm for extracting decision-making policies from Quantified Answer Set Programs, extending the interpretability of QASP models by linking them to policy representations.

Contribution

It presents the first algorithm for policy extraction from QASP models, inspired by Equilibrium Logic semantics, enhancing understanding of decision strategies in QASP.

Findings

Algorithm successfully extracts policies from QASP models

Demonstrates the interpretability of QASP in decision-making contexts

Bridges QASP models with policy representation frameworks

Abstract

Quantified Answer Set Programming (QASP) extends Answer Set Programming (ASP) by allowing quantification over propositional variables, similar to Quantified Boolean Formulas (QBF). In this paper, we interpret models of QASP formulas in terms of policies, which represent decision-making strategies that determine how existentially quantified variables should be assigned, given the conditions set by universally quantified variables. As a main contribution, we present an algorithm for policy extraction under QASP semantics, inspired by the Equilibrium Logic semantics for general ASP theories.