
Reinforcement Learning Specialization
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1. Course Introduction
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2. The K-Armed Bandit Problem
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3. What to Learn? Estimating Action Values
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4. Exploration vs. Exploitation Tradeoff
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Programming Assignment: Bandits and Exploration Exploitation
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Quiz
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1. Introduction to Markov Decision Processes
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2. Goal of Reinforcement Learning
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3. Continuing Tasks
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Quiz
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1. Policies and Value Functions
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2. Bellman Equations
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3. Optimality (Optimal Policies & Value Functions)
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Graded Quiz
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Practice Quiz
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1. Policy Evaluation (Prediction)
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2. Policy Iteration (Control)
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3. Generalized Policy Iteration
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4. Course Wrap-up
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Programming Assignment: Optimal Policies with Dynamic Programming
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Quiz
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1. Course Introduction
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2. Introduction to Monte Carlo Methods
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3. Monte Carlo for Control
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4. Exploration Methods for Monte Carlo
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5. Off-policy Learning for Prediction
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Programming Assignment: Blackjack
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Quiz
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1. Introduction to Temporal Difference Learning
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2. Advantages of TD
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Assigment
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Quiz
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1.TD for Control
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2. Off-policy TD Control: Q-learning
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3. Expected Sarsa
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Assigment
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Quiz
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1. What is a Model?
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2. Planning
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3. Dyna as a formalism for planning
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4. Dealing with inaccurate models
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Assigment
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5. Course Wrap-up
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Quiz
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1. Course 3 Introduction
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2. Estimating values functions with supervised learning
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3. The Objective for On-policy Prediction
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4. The Object for TD
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5. Linear TD
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Assigment
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Quiz
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1. Feature Construction for Linear Methods
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2. Neural Networks
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3. Training Neural Networks
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Assigment
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Quiz
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1. Episodic Sarsa with Function Approximation
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2. Exploration under Function Approximation
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3. Average Reward
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Programming Assignment: Function Approximation and Control
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Quiz
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1. Learning Parameterized Policies
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2. Policy Gradient for Continuing Tasks
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3. Actor-Critic for Continuing Tasks
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4. Policy Parameterizations
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Assigment
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5. Course Wrap-up
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Quiz
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1. Course Introduction
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1. Final Project: Milestone 1
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2. Project Resources
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Assigment
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1. Weekly Learning Goals
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2.Project Resources
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Quiz
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1. Weekly Learning Goals
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2. Project Resources
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Quiz
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1. Weekly Learning Goals
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2. Project Resources
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Assigment
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1. Weekly Learning Goals
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2. Project Resources
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Assigment
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3. Congratulations!
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