Complexity of Nested Circumscription and Nested Abnormality Theories
<|reference_start|>Complexity of Nested Circumscription and Nested Abnormality Theories: The need for a circumscriptive formalism that allows for simple yet elegant modular problem representation has led Lifschitz (AIJ, 1995) to introduce nested abnormality theories (NATs) as a tool for modular knowledge representation, tailored for applying circumscription to minimize exceptional circumstances. Abstracting from this particular objective, we propose L_{CIRC}, which is an extension of generic propositional circumscription by allowing propositional combinations and nesting of circumscriptive theories. As shown, NATs are naturally embedded into this language, and are in fact of equal expressive capability. We then analyze the complexity of L_{CIRC} and NATs, and in particular the effect of nesting. The latter is found to be a source of complexity, which climbs the Polynomial Hierarchy as the nesting depth increases and reaches PSPACE-completeness in the general case. We also identify meaningful syntactic fragments of NATs which have lower complexity. In particular, we show that the generalization of Horn circumscription in the NAT framework remains CONP-complete, and that Horn NATs without fixed letters can be efficiently transformed into an equivalent Horn CNF, which implies polynomial solvability of principal reasoning tasks. Finally, we also study extensions of NATs and briefly address the complexity in the first-order case. Our results give insight into the ``cost'' of using L_{CIRC} (resp. NATs) as a host language for expressing other formalisms such as action theories, narratives, or spatial theories.<|reference_end|>
@article{cadoli2002complexity,
    title={Complexity of Nested Circumscription and Nested Abnormality Theories},
    author={Marco Cadoli, Thomas Eiter, and Georg Gottlob},
    journal={arXiv preprint arXiv:cs/0207072},
    year={2002},
    number={INFSYS RR-1843-02-10, Institut f. Informationssysteme, TU Vienna,
  2002},
    archivePrefix={arXiv},
    eprint={cs/0207072},
    primaryClass={cs.AI cs.CC cs.LO}
}