Probabilistic Planning in Hybrid Probabilistic Logic Programs
SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
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SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
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SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
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ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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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
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
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
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This paper presents a novel revision of the framework of Hybrid Probabilistic Logic Programming, along with a complete semantics characterization, to enable the encoding of and reasoning about real-world applications. The language of Hybrid Probabilistic Logic Programs framework is extended to allow the use of non-monotonic negation, and two alternative semantical characterizations are defined: stable probabilistic model semantics and probabilistic well-founded semantics. These semantics generalize the stable model semantics and well-founded semantics of traditional normal logic programs, and they reduce to the semantics of Hybrid Probabilistic Logic programs for programs without negation. It is the first time that two different semantics for Hybrid Probabilistic Programs with non-monotonic negation as well as their relationships are described. This proposal provides the foundational grounds for developing computational methods for implementing the proposed semantics. Furthermore, it makes it clearer how to characterize non-monotonic negation in probabilistic logic programming frameworks for commonsense reasoning.