Abstract
In [22], a new Hybrid Probabilistic Logic Programs framework has been proposed, and a new semantics has been developed to enable encoding and reasoning about real-world applications. In this paper, the language of Hybrid Probabilistic Logic Programs framework of [22] is extended to allow non-monotonic negation, and two alternative semantics are defined: stable probabilistic model semantics and probabilistic well-founded semantics. Stable probabilistic model semantics and probabilistic well-founded semantics generalize stable model semantics and well-founded semantics of traditional normal logic programs, and they reduce to the semantics of original Hybrid Probabilistic Logic programs framework of [22] 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 development provides a foundational ground for developing computational methods for computing the proposed semantics. Furthermore, it makes it clearer how to characterize non-monotonic negation in probabilistic logic programming frameworks for commonsense reasoning.
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Saad, E., Pontelli, E. (2005). Hybrid Probabilistic Logic Programs with Non-monotonic Negation. In: Gabbrielli, M., Gupta, G. (eds) Logic Programming. ICLP 2005. Lecture Notes in Computer Science, vol 3668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562931_17
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DOI: https://doi.org/10.1007/11562931_17
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