Mohamed Ali Eita

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...