作者: Yi-Dong Shen , Kewen Wang , Thomas Eiter , Michael Fink , Christoph Redl
DOI: 10.1016/J.ARTINT.2014.05.001
关键词: Constructive 、 Mathematics 、 Reduct 、 Computational complexity theory 、 Theoretical computer science 、 Non-monotonic logic 、 Description logic 、 Answer set programming 、 Knowledge representation and reasoning 、 Stable model semantics 、 Artificial intelligence
摘要: The answer set semantics presented by Faber et al. [27] has been widely used to define so called FLP sets for different types of logic programs. However, it was recently observed that when being extended from normal more general classes programs, this approach may produce with circular justifications are caused self-supporting loops. main reason behavior is the not fully constructive a bottom up construction sets. In paper, we overcome problem enhancing level mapping formalism such every I can be built fixpoint iteration one-step provability operator (more precisely, an van Emden-Kowalski reduct fΠI). This inspired fact under standard semantics, each program Π obtainable Gelfond-Lifschitz ΠI, which induces mapping. enhanced sets, call well-justified thanks free justifications. As framework, applies programs first-order formulas, aggregates, description hex-programs etc., provided rule satisfaction properly We study in depth computational complexity and Our results show does increase worst-case Furthermore, describe implementation report about experimental evaluation, indicates potential performance improvements practice.