Extracting Policies from Quantified Answer Set Programs

2026-01-07

Electronic Proceedings in Theoretical Computer Science

AI Summary

This work investigates how to extract interpretable decision strategies from Quantified Answer Set Programs (QASPs)—that is, rules that prescribe assignments to existentially quantified variables given fixed values of universally quantified variables. To this end, it establishes, for the first time, a formal connection between the model semantics of QASP and the notion of strategy, and proposes a strategy extraction algorithm grounded in equilibrium logic semantics. The approach not only provides a formal characterization of how existential variables respond to universal variables but also substantially enhances the interpretability and practical applicability of QASP. By offering an operational formal representation of decision-making processes within complex logical programs, this research advances the capacity to reason about and deploy quantified nonmonotonic reasoning in real-world scenarios.

Technology Category

• Knowledge Representation and Reasoning: Qualitative Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Multiagent Systems: Mechanism Design

Application Category

• Semantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semantics
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs

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.

Problem

• Quantified Answer Set Programming
• policy extraction
• existential quantification
• universal quantification
• decision-making strategies

Innovation

• Quantified Answer Set Programming
• Policy Extraction
• Equilibrium Logic
• Decision Strategies
• Quantified Boolean Formulas