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Adaptive Estimated Maximum-Entropy Distribution Model, L Tan, D Taniar

Dr Ling Tan

The Estimation of Distribution Algorithm (EDA) model is an optimization procedure through learning and sampling a conditional probabilistic function. The use of conditional density function permits multivariate dependency modelling, which is not captured in a population-based representation, like the classical Genetic Algorithms. The Gaussian model is a simple and widely used model for density estimation. However, an assumption of normality is not realistic for many real-life problems. Alternatively, the maximum-entropy model can be used, which makes no assumption of a normal distribution. One disadvantage of the maximum-entropy model is the learning cost of its parameters. This paper proposes an Adaptive …