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Hesham Magdy

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#reinforcement learning Open access Sep 2026

A comparative study of evolutionary algorithms and activation functions in neuroevolution deep reinforcement learning

NeuroEvolution is scalable alternative for gradient-based deep reinforcement learning, which provides parallel, gradient-free optimization that overcomes backpropagation’s limitations. However, the selection of the neural network activation function has a significant impact on the stability and rewards of evolutionary...

Hesham Magdy, Amany M. Sarhan, E. Sallam et al. · 0 citations

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