演算式決策與學習專題

Algorithmic game theory and learning are active interdisciplinary research areas with contributions from theoretical computer science, economics, networking, artificial intelligence, operations research, and discrete mathematics. In this course, we aim to further look into the rich literature and most updated developments or progress by reviewing the papers from the top conferences and journals related to the areas, and expect students to form their own research proposals.

Algorithmic Decision and Learning, or Algorithmic Mechanism Design and Social Choice

Literature review: paper reading, presentation, and critique multiple times (60%) Research Proposal and presentation (40%)

Literature review: paper reading, presentation, and critique multiple times (60%) Research Proposal and presentation (40%)

• Price of Anarchy and Games
• Information Cascading
• Mechanism Design
• Privacy in Mechanism Design
• Altruism in Games and Mechanisms
• Dynamics and Learning
• Research proposal

Conference papers mainly from ACM Conference on Economics and Computation, Conference on Web and Internet Economics, International Conference on Autonomous Agents and Multiagent Systems, Symposium on Algorithmic Game Theory, Symposium on Theory of Computing, etc. Journal papers mainly from Games and Economic Behavior, International Journal of Game Theory, ACM Transactions on Economics and Computation, etc.

地點

MB301

時間

每週下課後

聯絡方式

poanchen@nctu.edu.tw