Deep Reinforcement Learning Doesn't Work Yet

June 24, 2018 note: If you want to cite an example from the post, please cite the paper which that example came from. If you want to cite the post as a whole, you can use the following BibTeX:

June 24, 2018 note: If you want to cite an example from the post, please cite the paper which that example came from. If you want to cite the post as a whole, you can use the following BibTeX: @misc{rlblogpost, title={Deep Reinforcement Learning Doesn't Work Yet}, author={Irpan, Alex}, howpublished={\url{https://www.alexirpan.com/2018/02/14/rl-hard.html}}, year={2018} } This mostly cites papers from Berkeley, Google Brain, DeepMind, and OpenAI from the past few years, because that work is most visible to me. I’m almost certainly missing stuff from older literature and other institutions, and f

related reading

• Deep Reinforcement Learning: Pong from Pixelskarpathy.github.io
• Debugging Reinforcement Learning Systemsandyljones.com
• A (Long) Peek into Reinforcement Learning | Lil'Loglilianweng.github.io
• Deep Reinforcement Learning: Pong from Pixelskarpathy.github.io
• Key Papers in Deep RL - Spinning Up documentationspinningup.openai.com
• Reward is not the optimization target — LessWronglesswrong.com
• [1709.06560] Deep Reinforcement Learning that Mattersarxiv.org
• Just Ask for Generalization | Eric Jangevjang.com
• Q-learning is not yet scalableseohong.me
• RLHF: Reinforcement Learning from Human Feedbackhuyenchip.com
• Deep Reinforcement Learning from Human Preferencesproceedings.neurips.cc
• You can’t imitation-learn how to continual-learn — LessWronglesswrong.com