IERG 5350 2020-2021 Term 1

Reinforcement Learning
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The schedule is being updated.

Week Time Topic Materials
Week 1 Mon Course overview slide
Tue RL basics and coding with RL slide,code
Week 2 Mon Markov decision process slide,project
Tue Policy iteration and value iteration slide,code,HW1 out
Week 3 Mon Model-free prediction slide
Tue Model-free control slide, course proposal due
Week 4 Mon On-policy learning and off-policy learning slide
Tue Connection to optimal control slide, HW1 due, HW2 out
Week 5 Mon Value function approximation slide
Tue Deep Q Learning slide
Week 6 Mon Policy optimization I slide
Tue Policy optimization I HW2 due, HW3 out
Week 7 Mon Policy optimization II slide
Tue Policy optimization II
Week 8 Chung Yeung Holiday (no class)
Tue Policy optimization III slide, HW3 due, HW4 out
Week 9 Mon Exploration and exploitation slide
Tue Model-based Reinforcement Learning slide, project mid-term review
Week 10 Mon Guest Lecture by Tony Qin (Didi Research): RL in transportation
Tue Distributed computing and RL system design slide, HW4 due, HW5 out
Week 11 Mon Imitation learning slide
Tue Realworld RL and offline RL slide
Week 12 Mon Guest Lecture by Yuandong Tian (Facebook AI): Challenges in RL slide
Tue Advanced topics by Zhenghao Peng and Hao Sun Zhenghao's slide, Sun Hao's slide, HW5 due
Week 13 Mon Course Summary slide
Tue Course Summary
Week 14 Mon Student project final presentation
Tue Student project final presentation