Bibliography (13):

1. A domain-specific supercomputer for training deep neural networks

2. IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

3. MuZero: Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

4. Discovering Reinforcement Learning Algorithms

5. DeepMind Lab

6. https://mujoco.org/

7. SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference

8. Playing Atari with Deep Reinforcement Learning

9. Wikipedia Bibliography:

   1. https://en.wikipedia.org/wiki/Google_JAX  :

      https://en.wikipedia.org/wiki/Google_JAX

   2. Reinforcement learning

   3. https://en.wikipedia.org/wiki/Project_Jupyter#Industry_adoption  :

      https://en.wikipedia.org/wiki/Project_Jupyter#Industry_adoption

   4. https://en.wikipedia.org/wiki/Atari_videogame_Pong  :

      https://en.wikipedia.org/wiki/Atari_videogame_Pong

   5. Monte Carlo tree search