Discrete Action On-Policy Learning with Action-Value Critic
AISTATS, pp. 1977-1987, 2020.
Reinforcement learning (RL) in discrete action space is ubiquitous in real-world applications, but its complexity grows exponentially with the action-space dimension, making it challenge to apply existing on-policy gradient based deep RL algorithms efficiently. To effectively operate in multidimensional discrete action spaces, we constr...More
PPT (Upload PPT)