What is wrong with reinforcement learning? (Ep. 82)

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After reinforcement learning agents doing great at playing Atari video games, Alpha Go, doing financial trading, dealing with language modeling, let me tell you the real story here.
In this episode I want to shine some light on reinforcement learning (RL) and the limitations that every practitioner should consider before taking certain directions. RL seems to work so well! What is wrong with it?

 

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References

• Emergence of Locomotion Behaviours in Rich Environments 
  https://arxiv.org/abs/1707.02286
• Rainbow: Combining Improvements in Deep Reinforcement Learning 
  https://arxiv.org/abs/1710.02298
• AlphaGo Zero: Starting from scratch 
  https://deepmind.com/blog/article/alphago-zero-starting-scratch