Sol-A Kim

Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling

Many real-world applications of reinforcement learning require an agent to select optimal actions from continuous spaces. Recently, deep neural networks have successfully been applied to games with discrete actions spaces. However, deep neural networks for discrete actions are not suitable for devis…