課程資訊
課程名稱
不完全資訊賽局
Games with Incomplete Information 
開課學期
108-1 
授課對象
社會科學院  經濟學研究所  
授課教師
班哲明 
課號
ECON7219 
課程識別碼
323EM1680 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期三6,7,8(13:20~16:20) 
上課地點
社科研609 
備註
本課程以英語授課。
限碩士班以上 或 限博士班
總人數上限:20人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1081ECON7219 
課程簡介影片
 
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課程大綱
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課程概述

From job applications to selling goods or playing poker, there are many situations in which a strategic decision maker has only some, but not all the payoff-relevant information. Uninformed players then maximize their utility according to their beliefs about the unknown quantity. This course provides the tools to describe such incomplete information games and introduces commonly used solution concepts. In addition to the static environment, we study mechanism design, where the principal designs the environment, and dynamic/repeated environments, where players have the ability to learn over time. 

課程目標
Students will be able to recognize and model situations with incomplete information and use the right tools/solution concepts to solve them.

Course outline (Course Schedule of 18 weeks)
Week 1: Introduction
Week 2: Harsanyi's equivalence, Bayesian Nash equilibrium
Week 3: Higher-order beliefs, type spaces, interim correlated rationalizability
Week 4: Bounded rationality
Week 5: Applications: auctions, Bayesian persuasion
Week 6: Mechanism design: revelation principle, implementability
Week 7: Mechanism design: efficiency, robustness
Week 8: Applications of mechanism design: screening, auctions
Week 9: Midterm exam
Week 10: Dynamic games: perfect Bayesian Nash equilibrium, sequential equilibrium
Week 11: Dynamic games: trembling-hand perfection, interim sequential rationalizability
Week 12: Principal-agent models: adverse selection, signaling
Week 13: Repeated games: reputation effects
Week 14: Repeated games: sequential bargaining
Week 15: Dynamic mechanism design
Week 16: Stochastic games: Markov perfect equilibrium
Week 17: Stochastic games: applications
Week 18: Final exam
 
課程要求
Requirements for students after the class:
Students will be able to recognize and model situations with incomplete information and use the right tools/solution concepts to solve them. 
預期每週課後學習時數
 
Office Hours
每週三 16:20~17:20 備註: Or by appointment 
指定閱讀
Required readings
“Game Theory”, 1st edition, 1991, by Drew Fudenberg and Jean Tirole, MIT Press  
參考書目
Extension readings
“An Introduction to Modern Mechanism Design”, 1st edition, 2015, by Tilman Börgers, Oxford University Press 
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Assignments 
20% 
 
2. 
Midterm exam 
30% 
or 20% if the grade is worse than the final grade 
3. 
Final examination 
50% 
or 60% if the grade is better than the midterm grade. The final examination consists of a group project and a conventional exam, both contributing equally to the grade. Some in-class time will be given to work on the project. 
 
課程進度
週次
日期
單元主題
第1週
9/11  Introduction 
第2週
9/18  Harsanyi's equivalence, Bayesian Nash equilibrium 
第3週
9/25  Higher-order beliefs, type spaces, interim correlated rationalizability 
第4週
10/02  Bounded rationality 
第5週
10/09  Applications: auctions, Bayesian persuasion 
第6週
10/16  Mechanism design: revelation principle, implementability 
第7週
10/23  Mechanism design: efficiency, robustness 
第8週
10/30  Applications of mechanism design: screening, auctions 
第9週
11/06  Midterm exam 
第10週
11/13  Dynamic games: perfect Bayesian Nash equilibrium, sequential equilibrium 
第11週
11/20  Dynamic games: trembling-hand perfection, interim sequential rationalizability 
第12週
11/27  Principal-agent models: adverse selection, signaling 
第13週
12/04  Repeated games: reputation effects 
第14週
12/11  Repeated games: sequential bargaining 
第15週
12/18  Dynamic mechanism design 
第16週
12/25  Stochastic games: Markov perfect equilibrium 
第17週
1/01  Stochastic games: applications 
第18週
1/08  Final exam