{"product_id":"foundations-of-probabilistic-logic-programming-languages-semantics-inference-and-learning-hardcover","title":"Foundations of Probabilistic Logic Programming: Languages, Semantics, Inference and Learning - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eFabrizio Riguzzi\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eProbabilistic 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.\u003c\/p\u003e\u003cp\u003eLogic 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.\u003c\/p\u003e\u003cp\u003eProbabilistic 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.\u003c\/p\u003e\u003cp\u003eProbabilistic 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.\u003c\/p\u003e\u003cp\u003eSince its birth, the field of Probabilistic Logic Programming has seen a steady increase of activity, with many proposals for languages and algorithms for inference and learning. \u003cem\u003eFoundations of Probabilistic Logic Programming \u003c\/em\u003eaims at providing an overview of the field with a special emphasis on languages under the Distribution Semantics, one of the most influential approaches. The book presents the main ideas for semantics, inference, and learning and highlights connections between the methods.\u003c\/p\u003e\u003cp\u003eMany examples of the book include a link to a page of the web application http: \/\/cplint.eu where the code can be run online.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 422\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.94 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 01, 2018\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":50499248750840,"sku":"9788770220187","price":193.3,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0698\/5629\/7208\/files\/79C3N6OGpy9788770220187.webp?v=1789285971","url":"https:\/\/barneysbooksellers.com\/products\/foundations-of-probabilistic-logic-programming-languages-semantics-inference-and-learning-hardcover","provider":"Barney's Book Sellers","version":"1.0","type":"link"}