Cross entropy10/6/2023 Optimization of Computer simulation Models with Rare Events, European Journal of Operational Research, 99, 89–112. Annals of Operations Research, 134 (1), 19–67. De Boer, P-T., Kroese, D.P, Mannor, S. ![]() Return mean of final sampling distribution as solution return μ Update parameters of sampling distribution Sort X by objective function values in descending order Evaluate objective function at sampled points While maxits not exceeded and not converged while t ε do // Obtain N samples from current sampling distribution This yields the following randomized algorithm that happens to coincide with the so-called Estimation of Multivariate Normal Algorithm (EMNA), an estimation of distribution algorithm. The worst of the elite samples is then used as the level parameter for the next iteration. Neal, in which there is an early use of the term 'Hemholtz Machine' - possibly the first. The method has also been applied to the traveling salesman, quadratic assignment, DNA sequence alignment, max-cut and buffer allocation problems.Įstimation via importance sampling Ĭonsider the general problem of estimating the quantity As far as the origin of the term 'cross entropy' relates to artificial neural networks, there is a term used in a paper in Science, submitted 1994, published 1995, by G. Reuven Rubinstein developed the method in the context of rare event simulation, where tiny probabilities must be estimated, for example in network reliability analysis, queueing models, or performance analysis of telecommunication systems.
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