Quantitative deduction and its fixpoint theory
Journal of Logic Programming
Bilattices and the semantics of logic programming
Journal of Logic Programming
Theory of generalized annotated logic programming and its applications
Journal of Logic Programming
Probabilistic logic programming
Information and Computation
Stable semantics for probabilistic deductive databases
Information and Computation
Computing annotated logic programs
Proceedings of the eleventh international conference on Logic programming
Probabilistic deductive databases
ILPS '94 Proceedings of the 1994 International Symposium on Logic programming
An algorithm for probabilistic planning
Artificial Intelligence - Special volume on planning and scheduling
Uncertain deductive databases: a hybrid approach
Information Systems
A Parametric Approach to Deductive Databases with Uncertainty
IEEE Transactions on Knowledge and Data Engineering
On the Semantics of Rule-Based Expert Systems with Uncertainty
ICDT '88 Proceedings of the 2nd International Conference on Database Theory
Adaptive Bayesian Logic Programs
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Modeling Uncertainty in Deductive Databases
DEXA '94 Proceedings of the 5th International Conference on Database and Expert Systems Applications
PRISM: a language for symbolic-statistical modeling
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Logic programs with uncertainties: a tool for implementing rule-based systems
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Hybrid probabilistic programs: algorithms and complexity
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Probabilistic Planning in Hybrid Probabilistic Logic Programs
SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
A Logical Framework to Reinforcement Learning Using Hybrid Probabilistic Logic Programs
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
A Logical Approach to Qualitative and Quantitative Reasoning
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Probabilistic Reasoning by SAT Solvers
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Probabilistic Planning with Imperfect Sensing Actions Using Hybrid Probabilistic Logic Programs
SUM '09 Proceedings of the 3rd International Conference on Scalable Uncertainty Management
Extended Fuzzy Logic Programs with Fuzzy Answer Set Semantics
SUM '09 Proceedings of the 3rd International Conference on Scalable Uncertainty Management
Query Answering in Belief Logic Programming
SUM '09 Proceedings of the 3rd International Conference on Scalable Uncertainty Management
Towards the computation of stable probabilistic model semantics
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
New advances in logic-based probabilistic modeling by PRISM
Probabilistic inductive logic programming
Disjunctive fuzzy logic programs with fuzzy answer set semantics
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Hybrid probabilistic logic programs with non-monotonic negation
ICLP'05 Proceedings of the 21st international conference on Logic Programming
Incomplete knowledge in hybrid probabilistic logic programs
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
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The hybrid probabilistic programs framework [1] allows the user to explicitly encode both logical and statistical knowledge available about the dependency among the events in the program. In this paper, we extend the language of hybrid probabilistic programs by allowing disjunctive composition functions to be associated with heads of clauses, and we modify its semantics to make it more suitable to encode real-world applications. The new semantics is a natural extension of standard logic programming semantics. The new semantics of hybrid probabilistic programs also subsumes the implication-based probabilistic approach proposed by Lakshmanan and Sadri [12]. We provide also a sound and complete algorithm to compute the least fixpoint of hybrid probabilistic programs with annotated atomic formulas as rule heads.