AI & ML Research Papers

Sigmoid-weighted linear units for neural network function approximation in reinforcement learning

Stefan Elfwing, Eiji Uchibe, Kenji Doya

This paper proposes SiLU and dSiLU activation functions and demonstrates that on-policy Sarsa(λ) with softmax action selection can outperform DQN in Atari games without experience replay or target networks.