Welcome to the Final Capstone Course! -Course Introduction
Course 4 Introduction
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Meet your instructors!
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Reinforcement Learning Textbook
Pre-requisites and Learning Objectives
Milestone 1: Formalize Word Problem as MDP-Final Project: Milestone 1
Initial Project Meeting with Martha: Formalizing the Problem
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Andy Barto on What are Eligibility Traces and Why are they so named?
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Milestone 1: Formalize Word Problem as MDP-Project Resources
Let's Review: Markov Decision Processes
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Let's Review: Examples of Episodic and Continuing Tasks
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Milestone 2: Choosing The Right Algorithm-Weekly Learning Goals
Meeting with Niko: Choosing the Learning Algorithm
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Milestone 2: Choosing The Right Algorithm-Project Resources
Let's Review: Expected Sarsa
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Let's Review: What is Q-learning?
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Let's Review: Average Reward- A New Way of Formulating Control Problems
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Let's Review: Actor-Critic Algorithm
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Csaba Szepesvari on Problem Landscape
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Andy and Rich: Advice for Students
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Milestone 3: Identify Key Performance Parameters-Weekly Learning Goals
Agent Architecture Meeting with Martha: Overview of Design Choices
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Milestone 3: Identify Key Performance Parameters-Project Resources
Let's Review: Non-linear Approximation with Neural Networks
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Drew Bagnell on System ID + Optimal Control
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Susan Murphy on RL in Mobile Health
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Milestone 4: Implement Your Agent -Weekly Learning Goals
Meeting with Adam: Getting the Agent Details Right
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Milestone 4: Implement Your Agent -Project Resources
Let's Review: Optimization Strategies for NNs
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Let's Review: Expected Sarsa with Function Approximation
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Let's Review: Dyna & Q-learning in a Simple Maze
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Meeting with Martha: In-depth on Experience Replay
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Martin Riedmiller on The 'Collect and Infer' framework for data-efficient RL
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Milestone 5: Submit Your Parameter Study!-Weekly Learning Goals
Meeting with Adam: Parameter Studies in RL
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Milestone 5: Submit Your Parameter Study!-Project Resources
Let's Review: Comparing TD and Monte Carlo
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Joelle Pineau about RL that Matters
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Milestone 5: Submit Your Parameter Study!-Congratulations!
Meeting with Martha: Discussing Your Results
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Course Wrap-up
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Specialization Wrap-up
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