2019-2020 2nd term, IERG 6130

Reinforcement Learning and Beyond
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The schedule is being updated.

Week Time Topic Materials
Week 1 Tu 2:30pm-4:15pm Course overview and introduction of RL slide
Wed 3:30pm-4:15pm Get hand dirty by coding slide, code
Week 2 Tu 2:30pm-4:15pm Markov decision process slide
Wed 3:30pm-4:15pm Policy iteration and value iteration slide, code, HW1 out
Week 3 Tu 2:30pm-4:15pm Model-free prediction slide
Wed 3:30pm-4:15pm Model-free control slide, proposal due
Week 4 - Chinese New Year Holiday
- Chinese New Year Holiday
Week 5 Tu 2:30pm-4:15pm Review on Tabular RL slide
Wed 3:30pm-4:15pm On-policy learning and off-policy learning slide, HW1 due
Week 6 Tu 2:30pm-4:15pm Value function approximation slide
Wed 3:30pm-4:15pm Deep Q Learning slide, HW2 out
Week 7 Tu 2:30pm-4:15pm Policy optimization I slide
Wed 3:30pm-4:15pm Policy optimization II slide
Week 8 Tu 2:30pm-4:15pm Student project mid-term presentation
Wed 3:30pm-4:15pm Policy optimization III: variants of actor-critic and code slide, HW2 due, HW3 out
Week 9 Tu 2:30pm-4:15pm Policy optimization IV: state of the arts 1 slide
Wed 3:30pm-4:15pm Policy optimization IV: state of the arts 2 slide
Week 10 Tu 2:30pm-4:15pm Model-based Reinforcement Learning slide
Wed 3:30pm-4:15pm Imitation Learning slide, HW3 due, HW4 out
Week 11 Tu 2:30pm-4:15pm Distributed computing and RL system design slide
Wed 3:30pm-4:15pm Exploration and exploitation slide
Week 12 Tu 2:30pm-4:15pm GameAI and AlphaGo series slide
Wed 3:30pm-4:15pm Real-World RL slide
Week 13 Tu 2:30pm-4:15pm Generative Modeling slide
Wed 3:30pm-4:15pm Supervised and Self-supervised Feature Learning slide
Week 14 Tu 2:30pm-4:15pm Course Summary slide, HW4 due
Wed 3:30pm-4:15pm Course Summary
Week 15 Tu 2:30pm-4:15pm Student project final presentation
Wed 3:30pm-4:15pm Student project final presentation