Huimin Han

Continuous Soft Actor-Critic: An Off-Policy Learning Method Robust to Time Discretization

Many \textit{Deep Reinforcement Learning} (DRL) algorithms are sensitive to time discretization, which reduces their performance in real-world scenarios. We propose Continuous Soft Actor-Critic, an off-policy actor-critic DRL algorithm in continuous time and space. It is robust to environment time d…