| 课程号 |
04833550 |
学分 |
2 |
| 英文名称 |
Economics and Computation |
| 先修课程 |
The course only requires basic knowledge in algorithms. No background in Economics is necessary. |
| 中文简介 |
经济与计算（非计算经济学）是近年新兴的热门交叉学科。它涵盖经济学，理论计算机科学，以及人工智能等。本课程将为经济与计算领域提供一个由浅入深的介绍，解释相关经济学原理（包括十多位诺贝尔经济学奖得主的核心工作），算法理论，计算思想，以及人工智能（包括算法博弈论和计算社会选择理论）。 我们将详细讨论一些关键的算法，协议，以及热门应用，如众包（crowdsourcing）和比特币 。 |
| 英文简介 |
Economics and Computation is an emerging multi-disciplinary field of Economics, Theoretical Computer Science, and Artificial Intelligence. It brings together principles and methodologies in these fields to tackle challenges in the internet era. This course offers a comprehensive in-depth introduction to key subjects in Economics and Computation. It will cover great ideas in Economics, including key contributions of more than 10 Nobel laureates in economics, as well as computational techniques and computational thinking in new topics such as Algorithmic Game Theory and Computational Social Choice, which were recognized one of the eleven “fundamental methods and application areas” of AI, according to The One Hundred Year Study on Artificial Intelligence at Stanford University.
Students will learn (1) key applications of Economics and Computation, including social choice, auctions, matching and resource allocation; (2) important conceptual contributions, including Nash Equilibrium and their refinements, implementation theory, incentive analysis, discrete choice models; (3) technical breakthroughs and algorithms, such as the VCG mechanism, deferred acceptance algorithm, top-trading-cycles, generalized method-of-moments; (4) modern topics such as security games, crowdsourcing, bitcoins.
This course is based on a highly-rated course taught by Lirong for four times at RPI. |
| 开课院系 |
信息科学技术学院 |
| 通选课领域 |
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| 是否属于艺术与美育 |
否 |
| 平台课性质 |
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| 平台课类型 |
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| 授课语言 |
英文 |
| 教材 |
Economics and Computation,D. Parkes and S. Seuken；
Learning and Decision-Making from Rank Data,L. Xia；
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations,Y. Shoham and K. Leyton-Brown,2009,Algorithmic Game Theory,N. Nisan, T. Roughgarden, E. Tardos and V. Vazirani,2007,Handbook of Computational Social Choice,F. Brandt, V. Coniter, U. Endriss, J. Lang, A. Procaccia,2016, |
| 参考书 |
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| 教学大纲 |
1) 学生将在课程结束时知道经济与计算这一新兴交叉学科的重要性和基本原理，了解算法博弈论和计算社会选择理论的核心贡献和新的挑战。
2) 帮助学生理解和培养进行动机分析(incentive analysis)的能力。
Introduction: 1学时
Simultaneous-move games: 2学时
Sequential-move games and Bayesian games: 3学时
Algorithmic Game Theory: Equilibrium Computation: 3学时
Mechanism design: 3学时
Matching and resource allocation: 3学时
Voting: 3学时
Computational Social Choice: 3学时
Wisdom of the crowd: 3学时
Discrete Choice Models: 3学时
Crowdsourcing: 1学时
Blockchain and bitcoin: 2学时
Discussion and presentations: 2学时
课堂授课为主，课后练习、讨论及汇报为辅。
课堂参与和讨论（30%），作业（40%）, 考试（30％）
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| 教学评估 |
曹永知：
学年度学期：17-18-3，课程班：经济与计算1，课程推荐得分：4.42，教师推荐得分：4.42，课程得分分数段：85-90；
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