Rainbow: Combining Improvements in Deep Reinforcement Learning

Understand

The deep reinforcement learning community has made several independent improvements to the DQN algorithm.

• However, it is unclear which of these extensions are complementary and can be fruitfully combined.
• This paper examines six extensions to the DQN algorithm and empirically studies their combination.
• Our experiments show that the combination provides state-of-the-art performance on the Atari 2600 benchmark, both in terms of data efficiency and final performance.