Our slides: inverse/imitation rl; multi-agent 101; multi-agent 102; hierarchical rl
In this week you can find several sections covering advanced topics in RL, along with less advanced topics that we couldn't squeeze into the main track
- Learning by imitation - video, assignment(berkeley cs294)
- Inverse reinforcement learning
- Distributional RL - video
- Knowledge transfer in RL - video(berkeley cs294)
- Hierarchical reinforcemnt learning
- Multi-Agent reinforcement learning
- awesome_rl - a curated list of resources dedicated to reinforcement learning.
- junhyukoh's list
- muupan's list
- Courses:
- CS294: deep reinforcement learning
- Silver's RL course
- Sutton's book, 2nd edition
- Implementations of many basic RL algorithms (raw and/or tensorflow)
- Reddit: General ML, RL, CS294
- [This great link you could have contributed]