[ FreeCourseWeb ] Foundations of Probabilistic Logic Programming- Languages, Semantics, Inference and Learning [Hardcover]

[ FreeCourseWeb.com ] Foundations of Probabilistic Logic Programming: Languages, Semantics, Inference and Learning [Hardcover]

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2018 | ISBN: 8770220182 | English | 415 pages | PDF | 12 MB
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertain information by means of probability theory. Probabilistic Logic Programming is at the intersection of two wider research fields: the integration of logic and probability and Probabilistic Programming.

Logic enables the representation of complex relations among entities while probability theory is useful for model uncertainty over attributes and relations. Combining the two is a very active field of study. Probabilistic Programming extends programming languages with probabilistic primitives that can be used to write complex probabilistic models. Algorithms for the inference and learning tasks are then provided automatically by the system.

Probabilistic Logic Programming is at the same time a logic language, with its knowledge representation capabilities, and a Turing complete language, with its computation capabilities, thus providing the best of both worlds.

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