A course in reinforcement learning in the wild
An open course on reinforcement learning in the wild. Taught on-campus at HSE and YSDA and maintained to be friendly to online students (both english and russian).
FAQ: About the course, Technical issues thread, Lecture Slides, Online Student Survival Guide
Anonymous feedback form.
Virtual course environment:
The syllabus is approximate: the lectures may occur in a slightly different order and some topics may end up taking two weeks.
week01_intro Introduction
week02_value_based Value-based methods
week03_model_free Model-free reinforcement learning
recap_deep_learning - deep learning recap
week04_approx_rl Approximate (deep) RL
week05_explore Exploration
week06_policy_based Policy Gradient methods
week07_seq2seq Reinforcement Learning for Sequence Models
week08_pomdp Partially Observed MDP
week09_policy_II Advanced policy-based methods
week10_planning Model-based RL & Co
yet_another_week Inverse RL and Imitation Learning
Course materials and teaching by: [unordered]