ASEN 6519
Advanced Survey of Sequential Decision Making
Is Q-learning guaranteed to converge?
Under what conditions?
Which is more sample-efficient? Model-based or Model-free Reinforcement Learning?
How much computational power did AlphaGo use?
Do you need less for chess?
How much more do you need to learn StarCraft?
Learning Objectives
- Broad familiarity with range of algorithms
- Theoretical tools
- Communication (hard!)
- Open research topics (know and investigate)
How?
(Assignments)
- Presentations and in-class discussions (3 each)
- Short-Answer Quizzes
- Final Project
Schedule
Logistics: Survey
Will send out tomorrow; due by Midnight Thursday
Logistics: Paper Access
Advice: How to read a paper
Optional Presentation Template
Presentation Tips
- Tell the story of the paper - why does it matter? People remember stories, and we will all be better off if you can make it engaging.
- Use precision in your language (this takes practice)
- Practice
- Understand the important parts so that you can answer questions, and be honest if you don't
- Information density is crucial - use appear animations to guide attention
Auditing
Since the course relies on student participation, I prefer for students to enroll rather than audit.
If you intend to audit:
- Please email me.
- I request that you contribute a paper presentation.
Quick Intro
- Name
- Station (e.g. third year grad student in AERO)
- What you want to learn about
- Background
- Research focus
DMU++ Intro
By Zachary Sunberg
DMU++ Intro
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