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 of choice logic formulas is Θ 2 P-complete for QCL and CCL, while being Δ 2 P-complete for a newly introduced choice logic. The complexity of preferred model entailment for choice logic theories ranges from coNP to Π 2 P.
Algorithms for Sustainable Group Decision Making: P31890-N31 (Fonds zur Förderung der wissenschaftlichen Forschung (FWF))
Austrian Science Fund (FWF) Austrian Science Fund (FWF)