Algorithmic Game Theory, Mechanism Design and Computational Economics
Advanced Course, 2+1
Basic Information
Lecturer:  Yun Kuen Cheung (You may call me Marco.) 

Lectures:  Monday 4pm to 6pm, Room 021 in Building E1.4 
Tutor:  Bhaskar Ray Chaudhury 
Tutorials:  Alternating Tuesday 2pm to 4pm, Room 021 in Building E1.4 
Credits:  5 
Prerequisites:  The following knowledge is assumed from enrolled students:

Description
(Currently, we are giving a brief desciption to facilitate students' planning. We will update this decription with more details later.)
Games and markets arise wherever there are two or more agents competing for selfish benefits. In their enormous applications, "agents" can refer to humans, animals, computers, bacterias or even molecules.
In the past 20 years, the algorithmic/computational aspects of game/market/auction theory have grown to become a popular topic in (theoretical) computer science, economics, operational research, dynamical system, and more. In this course, we will discuss the very core of this exciting new research direction.
For ambitious students who want to develop rigorous theoretical training related to this topic, I can suggest extra materials for reading and thinking.
This course is divided into three parts.
In the first part, we cover some basic concepts in games and markets, including Zerosum Game and Generalsum Game, Nash Equilibrium, Market Equilibrium, Correlated Equilibrium and Regret Minimization. Algorithms for finding such equilibria in will be presented.
Concerning equilibrium, one fundamental question is how good an equilibrium is. Prisoner Dilemma is a canonical example to show that Nash Equilibrium can be very bad. Efficiency measures and techniques, e.g. Price of Anarchy and Smoothness, will be covered.
In the second part, we address another fundamental question concerning equilibrium: how an equilibrium is reached. We will introduce and study a number of simple game/market dynamics, e.g. Tatonnement and Proportional Response Dynamic, aiming to explain how equilibrium can be reached in a highly distributed environment, in which individual agents can access very limited local information only. We will also look into an interesting special case of Linear Fisher/Exchange market, for which nontrivial flowtype algorithms are developed.
In the third part, we focus on the prominent application of game theory in the digital era  design of auction, or what we call the Mechanism Design, e.g. eBay, Google ad auction, spectrum auction. In the simplest setting, there is an auctioneer selling a number of items, and there are many agents who are interested in those items. Mechanism design concerns
 the design of communication protocols between auctioneer and agents
 design of efficient (polytime, or even stricter time requirement due to practical applications) algorithms to decide the allocation of items which achieve good efficiency
 design of truthful mechanism which motivates agents not to be strategic on reporting their preferences
Online Reference
Our course will have some overlaps with the following materials. We will also provide selfcontained lecture notes in this webpage.
 Thomas Ferguson's text on "Game Theory"
 Tim Roughgarden's courses on "Algorithmic Game Theory" and "Frontiers in Mechanism Design"
 Jason Hartline's text on "Mechanism Design and Approximation"