Choice Logics and Their Computational Properties

Choice Logics and Their Computational Properties

Michael Bernreiter, Jan Maly, Stefan Woltran

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Main Track. Pages 1794-1800. https://doi.org/10.24963/ijcai.2021/247

Qualitative Choice Logic (QCL) and Conjunctive Choice Logic (CCL) are formalisms for preference handling, with especially QCL being well established in the field of AI. So far, analyses of these logics need to be done on a case-by-case basis, albeit they share several common features. This calls for a more general choice logic framework, with QCL and CCL as well as some of their derivatives being particular instantiations. We provide such a framework, which allows us, on the one hand, to easily define new choice logics and, on the other hand, to examine properties of different choice logics in a uniform setting. In particular, we investigate strong equivalence, a core concept in non-classical logics for understanding formula simplification, and computational complexity. Our analysis also yields new results for QCL and CCL. For example, we show that the main reasoning task regarding preferred models is ϴ₂P-complete for QCL and CCL, while being Δ₂P-complete for a newly introduced choice logic.
Keywords:
Knowledge Representation and Reasoning: Preference Modelling and Preference-Based Reasoning
Knowledge Representation and Reasoning: Computational Complexity of Reasoning
Knowledge Representation and Reasoning: Logics for Knowledge Representation