Economics and Computation
Economics and Computation
Lecturer: Jhuang-Jie Lin (林莊傑)
Email: josephcclin@mail.ntou.edu.tw
Phone: (02)24622192 #6684
Webpage: https://cse.ntou.edu.tw/p/412-1063-12349.php?Lang=zh-tw
Course ID: M57015FK
Credits: 3
Objective:
This course focuses on theoretical aspects of game theory and applications in economics and machine learning. We expect the students to learn solid theoretical foundation on game-theoretical related topics, such as solution concepts, fixed-point theorems, minimax principles, social choice, auctions, online learning algorithms, etc., and then catch-up the recent progress in this field by paper-studying and presentations.
Course Prerequisites: Algorithms, Calculus, Probability Theory.
Outline:
1. Introduction and Preliminaries
2. Minimax Principles
3. Equilibrium Concepts
4. Social Choice
5. A Sketch of Nash’s Theorem from Fixed Point Theorems
6. Auctions & Mechanism Design Basics
7. No-Regret Dynamics
Teaching Method: Lecturing, Discussion, Paper Presentations
Reference:
1. Twenty Lectures on Algorithmic Game Theory. Tim Roughgarden. Cambridge University Press. 2016.
2. Self-prepared slides.
Course Schedule (subject to change):
1. Introduction (1 week)
2. Preliminaries (1 week)
3. Minimax Principles (2 weeks)
4. Equilibrium Concepts (2 weeks)
5. Social Choice (1 week)
6. Nash''s Theorem and Fixed Point Theorems (3 weeks)
7. Auctions & Mechanism Design Basics (3 weeks)
8. No-Regret Dynamics (3 weeks)
9. Paper Presentations (2 weeks)
Evaluation:
1. Attendance (10%)
2. Assignments (40%)
3. Final paper presentations (50%)