Quantitative deduction and its fixpoint theory
Journal of Logic Programming
On the declarative semantics of deductive databases and logic programs
Foundations of deductive databases and logic programming
A fixpoint semantics for disjunctive logic programs
Journal of Logic Programming
Foundations of disjunctive logic programming
Foundations of disjunctive logic programming
Stable semantics for probabilistic deductive databases
Information and Computation
Probabilistic logic programming with conditional constraints
ACM Transactions on Computational Logic (TOCL)
Extending Disjunctive Logic Programming by T-norms
LPNMR '99 Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning
Many-Valued Disjunctive Logic Programs with Probabilistic Semantics
LPNMR '99 Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning
Computing Stable and Partial Stable Models of Extended Disjunctive Logic Programs
ICLP '94/NMELP '94 Selected papers from the Workshop on Non-Monotonic Extensions of Logic Programming
Many-Valued First-Order Logics with Probabilistic Semantics
Proceedings of the 12th International Workshop on Computer Science Logic
Probabilistic and Truth-Functional Many-Valued Logic Programming
ISMVL '99 Proceedings of the Twenty Ninth IEEE International Symposium on Multiple-Valued Logic
Probabilistic disjunctive logic programming
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Query answering in normal logic programs under uncertainty
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
Fundamenta Informaticae
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In this paper, we continue to explore many-valued disjunctive logic programs with probabilistic semantics. In particular, we newly introduce the least model state semantics for such programs. We show that many-valued disjunctive logic programs under the semantics of minimal models, perfect models, stable models, and least model states can be unfolded to equivalent classical disjunctive logic programs under the respective semantics. Thus, existing technology for classical disjunctive logic programming can be used to implement many-valued disjunctive logic programming. Using these results on unfolding many-valuedness, we then give many-valued fixpoint characterizations for the set of all minimal models and the least model state. We also describe an iterative fixpoint characterization for the perfect model semantics under finite local stratification.