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Jadavpur University, 2025: Introduction to Reinforcement Learning

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Session 21: Actor Critic based Policy Gradient, Safe RL, Planning, DYNA, Curriculum Learning

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Session 20: Deep Neural Networks, MLP, Backpropagation, Policy Gradient, REINFORCE

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Session 19: Asynchronous Q learning, Classification in ML, MLE, Logistic and Softmax Regression

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Session 18 Synchronous Q-learning, Model-free, based, tabular, with Linear Fn. Approx., Convergence

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Session 17: Off-Policy Evaluation of TD0 with linear function Approximation, Emphatic TD0

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Session 16 γ contraction, Banach's Fixed Point Theorem, How far is it far from the intended optimal

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Session 15 TD(0) convergence proof (contd), Point of Convergence of TD(0) (linear function approx.)

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Session 14: TD0 with linear function approximation, Glimpse at Stochastic Approximation Algorithm(1)

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Session 13: Function Approximation in RL, Policy Evaluation, SGD Monte Carlo, TD(0) Implementation

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Session 12: On Policy vs Off Policy Algorithms, Importance Sampling, Model-free Q learning, SARSA

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