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Course 4 Introduction
Meet your instructors!
Initial Project Meeting with Martha: Formalizing the Problem
Andy Barto on What are Eligibility Traces and Why are they so named?
Let's Review: Markov Decision Processes
Let's Review: Examples of Episodic and Continuing Tasks
Meeting with Niko: Choosing the Learning Algorithm
Let's Review: Expected Sarsa
Let's Review: What is Q-learning?
Let's Review: Average Reward- A New Way of Formulating Control Problems
Let's Review: Actor-Critic Algorithm
Csaba Szepesvari on Problem Landscape
Andy and Rich: Advice for Students
Agent Architecture Meeting with Martha: Overview of Design Choices
Let's Review: Non-linear Approximation with Neural Networks
Drew Bagnell on System ID + Optimal Control
Susan Murphy on RL in Mobile Health
Meeting with Adam: Getting the Agent Details Right
Let's Review: Optimization Strategies for NNs
Let's Review: Expected Sarsa with Function Approximation
Let's Review: Dyna & Q-learning in a Simple Maze
Meeting with Martha: In-depth on Experience Replay
Martin Riedmiller on The 'Collect and Infer' framework for data-efficient RL
Meeting with Adam: Parameter Studies in RL
Let's Review: Comparing TD and Monte Carlo
Joelle Pineau about RL that Matters
Meeting with Martha: Discussing Your Results