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Markov Logic Network: Probabilistic Logic, Markov Random Field, Satisfiability, Entailment, First-Order Logic, Well-Formed Formula, Real Number, Logical Connective - Brossura
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. A Markov logic network (or MLN) is a probabilistic logic which applies the ideas of a Markov network to first-order logic. Markov logic networks generalize first-order logic, in the sense that, in a certain limit, all unsatisfiable statements have a probability of zero, and the set of all entailed formulas have probability one. Briefly, it is a collection of formulas from first order logic, to each of which is assigned a real number, the weight. Taken as a Markov network, the vertices of the network graph are atomic formulas, and the edges are the logical connectives used to construct the formula. Each formula is considered to be a clique, and the Markov blanket is the set of formulas in which a given atom appears. A potential function is associated to each formula, and takes the value of one when the formula is true, and zero when it is false. The potential function is combined with the weight to form the Gibbs measure and partition function for the Markov network.
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Markov Logic Network : Probabilistic Logic, Markov Random Field, Satisfiability, Entailment, First-Order Logic, Well-Formed Formula, Real Number, Logical Connective
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. A Markov logicnetwork (or MLN) is a probabilistic logic which applies the ideas of aMarkov network to first-order logic. Markov logic networks generalizefirst-order logic, in the sense that, in a certain limit, allunsatisfiable statements have a probability of zero, and the set of allentailed formulas have probability one. Briefly, it is a collection offormulas from first order logic, to each of which is assigned a realnumber, the weight. Taken as a Markov network, the vertices of thenetwork graph are atomic formulas, and the edges are the logicalconnectives used to construct the formula. Each formula is considered tobe a clique, and the Markov blanket is the set of formulas in which agiven atom appears. A potential function is associated to each formulaand takes the value of one when the formula is true, and zero when it isfalse. The potential function is combined with the weight to form theGibbs measure and partition function for the Markov network. Codice articolo 9786131834080
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Markov Logic Network
Print on DemandDa: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. A Markov logicnetwork (or MLN) is a probabilistic logic which applies the ideas of aMarkov network to first-order logic. Markov logic networks generalizefirst-order logic, in the sense that, in a certain limit, allunsatisfiable statements have a probability of zero, and the set of allentailed formulas have probability one. Briefly, it is a collection offormulas from first order logic, to each of which is assigned a realnumber, the weight. Taken as a Markov network, the vertices of thenetwork graph are atomic formulas, and the edges are the logicalconnectives used to construct the formula. Each formula is considered tobe a clique, and the Markov blanket is the set of formulas in which agiven atom appears. A potential function is associated to each formulaand takes the value of one when the formula is true, and zero when it isfalse. The potential function is combined with the weight to form theGibbs measure and partition function for the Markov network.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Codice articolo 9786131834080
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