Reinforcement Learning
Reinforcement learning resources: control theory, multi-agent and continual learning, deep RL courses, and labs worth watching.
On this page
Here will be all important resources and content that I found useful while learning Reinforcement Learning.
Topics of Interest
- Continual Learning
- Learning in Multi Agent Systems
- Multi Goal Reinforcement Learning
- Application
- Robotics
- Healthcare
- Finance
Currently Doing
- Go through research institutes section
- Practice
- Learn Control Theory
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- Talks about Reproducibility, Re-usability & Robustness
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Readings
People and Groups
- Peter Abbeel
- Maria-Florina Balcan
- Auke Jan | BioRob
- Leila Wehbe
- Computation and Cognition Lab
- Learning and Dynamical Systems Group
- ETH AI Center
- EPFL AI
- MIT CSAIL
- Stanford Research Groups
- Richard Sutton's Group (University of Alberta)
- Emma Brunskill's Lab (Stanford University): RL with few samples
- Shimon Whiteson's Lab (University of Oxford)
- Doina Precup's Lab (McGill University): fundamental RL
- Jan Peters' Group (TU Darmstadt): site
- Frank Hutter's Lab (University of Freiburg): site
- Jürgen Schmidhuber's Group (IDSIA, Switzerland)