Adversary A3C for Robust Reinforcement Learning

Understand

Asynchronous Advantage Actor Critic (A3C) is an effective Reinforcement Learning (RL) algorithm for a wide range of tasks, such as Atari games and robot control.

• The agent learns policies and value function through trial-and-error interactions with the environment until converging to an optimal policy.
• Robustness and stability are critical in RL; however, neural network can be vulnerable to noise from unexpected sources and is not likely to withstand very slight disturbances.
• We note that agents generated from mild environment using A3C are not able to handle challenging environments.