Markov Logic Network
978-613-1-83408-0
6131834083
64
2010-07-30
29.00 €
eng
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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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