The Epistocracy algorithm is a self-adaptive, andmulti-population optimizer in which the evolution process takes place in parallel for many populations led by a council of leaders . The algorithm uses a stratified sampling method called LatinHypercube Sampling (LHS) to distribute the initial population more evenly . To avoid stagnationin poor local optima and to prevent a premature convergence, the algorithm uses multiple mechanisms such as dynamic and adaptive leadership based ongravitational force, dynamic population allocation and diversification, and regression-based leadershipadjustment . To investigate the performance and evaluate the reliability of the algorithm, we have used a set of multimodal benchmark functions, and then applied the algorithm to the MNIST dataset to further verify the accuracy, scalability, androbustness of the algorithms . Experimental results show that the Epistocratsalgorithm outperforms the state-of-the-art evolutionary and swarm

Author(s) : Seyed Ziae Mousavi Mojab, Seyedmohammad Shams, Hamid Soltanian-Zadeh, Farshad Fotouhi

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Keywords : algorithm - population - adaptive - epistocracy - based -

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