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Random Worlds and Maximum Entropy

1994
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The Journal of Artificial Intelligence Research
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Given a knowledge base KB containing first-order and statistical facts, we consider a principled method, called the random-worlds method, for computing a degree of belief that some formula Phi holds given KB. If we are reasoning about a world or system consisting of N individuals, then we can consider all possible worlds, or first-order models, withdomain {1,...,N} that satisfy KB, and compute thefraction of them in which Phi is true. We define the degree of belief to be the asymptotic value of

doi:10.1613/jair.61
fatcat:3mef4ugpxbhptk44jhfxfy4z3m