CrossEntropy Class

This class implements the noisy cross entropy method as described in the following article. Christophe Thiery, Bruno Scherrer.Improvements on Learning Tetris with Cross Entropy. International Computer Games Association Journal, ICGA, 2009, 32. The algorithm aims to minimize an objective function through stochastic search. It works iteratively until a certain stopping criteria is met. At each iteration, it samples a number of vectors from a Gaussian distribution and evaluates each of these against the supplied objective function. Based on the return value from the objective function, a subset of the the best ranked vectors are chosen to update the search parameters of the next generation. The mean of the Gaussian distribution is set to the centroid of the best ranked vectors, and the variance is set to the variance of the best ranked vectors in each individual dimension.

public class CrossEntropy : BaseOptimizer