mdp

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1. 1▶Lecture 2 | Multi-arm Bandits | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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2. 2▶[CS292F 2021 Spring] Statistical RL Lecture 15: Offline RL (Part IV) Uniform OPE (continues)StatRL Spring 2021Notes
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3. 3▶[CS292F 2021 Spring] Statistical RL Lecture 14: Offline RL (Part III) Uniform OPEStatRL Spring 2021Notes
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4. 4▶[CS292F 2021 Spring] Statistical RL Lecture 13: Offline RL (Part II) Curse of Horizon and MISStatRL Spring 2021Notes
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5. 5▶[CS292F 2021 Spring] Statistical RL Lecture 12: Offline RL (Part I) Offline Policy EvaluationStatRL Spring 2021Notes
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6. 6▶[CS292F 2021 Spring] Statistical RL Lecture 11: Linear MDPs (Part II) + Intro to Offline RLStatRL Spring 2021Notes
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7. 7▶[CS292F 2021 Spring] Statistical RL Lecture 10: Exploration in Linear MDPsStatRL Spring 2021Notes
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8. 8▶[CS292F 2021 Spring] Statistical RL Lecture 9: Exploration in Tabular MDPsStatRL Spring 2021Notes
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9. 9▶[CS292F 2021 Spring] Statistical RL Lecture 8: Linear BanditsStatRL Spring 2021Notes
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10. 10▶[CS292F 2021 Spring] Statistical RL Lecture 7: Exploration in BanditsStatRL Spring 2021Notes
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11. 11▶[CS292F 2021 Spring] Statistical RL Lecture 6: RL Algorithm III + Exploration IStatRL Spring 2021Notes
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12. 12▶[CS292F 2021 Spring] Statistical RL Lecture 5: RL Algorithm IIStatRL Spring 2021Notes
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13. 13▶[CS292F 2021 Spring] Statistical RL Lecture 4: MDP III and RL Algorithm IStatRL Spring 2021Notes
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14. 14▶[CS292F 2021 Spring] Statistical RL Lecture 3: MDP IIStatRL Spring 2021Notes
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15. 15▶[CS292F 2021 Spring] Statistical RL Lecture 2: MDP IStatRL Spring 2021Notes
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16. 16▶[CS292F 2021 Spring] Statistical RL Lecture 1: Intro and MDP basicsStatRL Spring 2021Notes
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17. 17▶Lecture 1 | Machine Learning Paradigms - An Overview | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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18. 18▶Lecture 13 | Value Iteration and Monte Carlo Prediction | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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19. 19▶Lecture 10 - Bellman Expectation Equations for MDP | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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20. 20▶Lecture 11 | Bellman Optimality Eqs | Policy Iteration | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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21. 21▶Lecture 12 | Convergence Proof of Policy Iteration | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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22. 22▶Lecture 4 - Regret Analysis of UCB Bandit algorithm | Reinforcement Learning | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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23. 23▶Lecture 5 - UCB Regret | KL Divergence | B–H inequality | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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24. 24▶Lecture 6 - Lower Bound on Regret for Bandit Algorithms | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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25. 25▶Lecture 7 - Thompson Sampling for Multi-arm Bandits | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT KanpurNotes
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26. 26▶Lecture 11 Probability Review, Bayes Filters, Gaussians -- CS287-FA19 Advanced RoboticsCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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27. 27▶Lecture 12 Kalman Filters -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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28. 28▶Lecture 13 Kalman Smoother, MAP, ML, EM -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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29. 29▶Lecture 14 Particle Filters -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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30. 30▶Lecture 15 Partially Observable MDPs (POMDPs) -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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31. 31▶Lecture 10 Motion Planning: PRM, RRT, Trajopt -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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32. 32▶Lecture 8 Optimization-based Control: Collocation, Shooting, MPC -- CS287-FA19 Advanced RoboticsCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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33. 33▶Lecture 3 Solving Continuous MDPs with Discretization -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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34. 34▶Lecture 4 MDPs and Function Approximation -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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35. 35▶Lecture 5 LQR -- CS287-FA19 Advanced Robotics at UC BerkeleyCS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter AbbeelNotes
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