| Abstract: |  This work describes the evolution strategy based on adaptation of covariance matrices for optimization in continuous space. The principle of algorithm dwells in gradual update of covariance matrix and in moving the mean value of normal distribution so as to achieve convergence to some optima in successive generations. This work proposes a detailed analysis of each step of the algorithm including the possible options or modifications and the known implementation. It also includes a description of CMA-ES, IPOP-CMA-ES and sigma-m-IPOP-CMA-ES implementations in Java programming language into JCool library. A series of experiments were performed using the method, comparing between algorithms available in JCool library, including the progress of algorithm on the selected test functions. |
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