Algorithmic Game Theory
( 24 Modules )

Module #1
Introduction to Algorithmic Game Theory
Overview of the course, motivations, and applications of algorithmic game theory

Module #2
Game Theory Basics
Review of game theory concepts:strategic games, Nash equilibrium, Pareto optimality

Module #3
Algorithmic Complexity in Games
Introduction to computational complexity theory and its relation to game theory

Module #4
Computing Nash Equilibrium
Algorithms for computing Nash equilibria in normal form games

Module #5
Nash Equilibrium in Extensive Form Games
Computing Nash equilibria in extensive form games with perfect information

Module #6
Mixed Strategies and Randomized Algorithms
Introduction to mixed strategies and randomized algorithms for computing Nash equilibria

Module #7
Mechanism Design Basics
Introduction to mechanism design:direct revelation, truthfulness, and implementation

Module #8
Mechanism Design for Single-Parameter Domains
Mechanism design for single-parameter domains:auctions, scheduling, and resource allocation

Module #9
Mechanism Design for Multi-Parameter Domains
Mechanism design for multi-parameter domains:combinatorial auctions and multidimensional mechanism design

Module #10
Approximation Algorithms for Mechanism Design
Approximation algorithms for mechanism design:FPTAS, PTAS, and hardness results

Module #11
Price of Anarchy
Introduction to the price of anarchy:quantifying the inefficiency of Nash equilibria

Module #12
Price of Anarchy in Congestion Games
Price of anarchy in congestion games:routing, network design, and facility location

Module #13
Price of Anarchy in Auctions
Price of anarchy in auctions:revenue maximization and auction design

Module #14
auction Theory
Introduction to auction theory:independent private values, common values, and correlated values

Module #15
Auction Design
Auction design:optimal auction design, revenue equivalence, and auction implementation

Module #16
Computing Optimal Auctions
Algorithms for computing optimal auctions:MIP, LP, and dynamic programming

Module #17
Online Algorithms for Game Theory
Introduction to online algorithms for game theory:online learning, regret minimization, and online auctions

Module #18
No-regret Algorithms for Game Theory
No-regret algorithms for game theory:multiplicative weights, EXP3, and online combinatorial optimization

Module #19
Game Theory and Machine Learning
Connections between game theory and machine learning:Nash equilibria, learning in games, and game-theoretic machine learning

Module #20
Game Theory and Networks
Game theory on networks:network games, network design, and diffusion models

Module #21
Game Theory and Economics
Applications of game theory in economics:general equilibrium, market design, and behavioral economics

Module #22
Game Theory and Computer Science
Applications of game theory in computer science:algorithm design, distributed systems, and cryptography

Module #23
Advanced Topics in Algorithmic Game Theory
Recent advances and open problems in algorithmic game theory:learning in games, robust mechanism design, and fairness in game theory

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Algorithmic Game Theory career

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Algorithmic Game Theory ( 24 Modules )

Algorithmic Game Theory
( 24 Modules )