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Department of Informatics Computation and Economics Research Group

Lecture: Economics and Computation (Fall 2017)

Lecturer: Prof. Dr. Sven Seuken
Teaching Assistants: Gianluca BreroLudwig DierksDmitry Moor, Mirko Richter
Teaching Language English
Level BSc, MSc
Academic Semester Fall 2017
Time and Location

Lecture: Wednesday 12:15-13:45

Room: BIN-2.A.10

Excercise Session: Thursday 12:15-13:45

Room: BIN-1.D.29

AP (ECTS): 6 (including a mark)
Office Hours Prof. Dr. Sven Seuken: email for appointments, BIN-2.B.02

Course Content

In this course, we will cover the interplay between economic thinking and computational thinking as it relates to electronic commerce in particular, and socio-economic systems in general. Topics covered include: game theory, mechanism design, p2p file-sharing, eBay auctions, advertising auctions, combinatorial auctions, matching markets, computational social choice, and crowdsourcing markets. Emphasis will be given to core methodologies necessary to design such systems with good economic and computational properties. Students will be engaged in theoretical, computational, and empirical exercises.


Lectures (tentative schedule)

Lecture Date Topic/Reading Fun & Interesting
1 Wed, 20.9.2017 Incentives
2 Wed, 27.9.2017 Game Theory (skip sections 2.5 and 2.6) Game Theory,
Primates & Game Theory ,
Badminton & Game Theory (jump to 15:00) (explanation) ,
Repeated Games
3 Wed, 04.10.2017 The Economics of P2P File Sharing Court...
4 Wed, 11.10.2017 Auction Theory and eBay (skip 6.4 and 6.5) eBay
5 Wed, 18.10.2017 Mechanism Design Part 1 (read 7.1 and 7.2, rest optional) Restaurant Pricing
6 Wed, 25.10.2017 Mechanism Design Part 2 (read 7.5 and 7.6, rest optional)  
7 Wed, 01.11.2017 Online Advertising Auctions (skip 10.6) Online Ads
8 Wed, 08.11.2017 Linear Programming (optional: 3.3 + 3.4)  
9 Wed, 15.11.2017 Integer Programming (optional: 12.2, 12.4, 12.7, 12.8)


10 Wed, 22.11.2017 Combinatorial Auctions (

optional 11.5 and 11.6)

11 Wed, 29.11.2017 Matching Markets

(optional 12.4.4 and 12.4.5 and 12.4.6)

Kidney Markets
12 Wed, 06.12.2017 Computational Social Choice Elections
13 Wed, 13.12.2017 Review  

Wed, 20.12.2017,

at 12:00-14:00

Final Exam (room BIN-2.A.10)  


Exercise Sessions (tentative schedule)

Section Date Topic
1 Thu, 21.09.2017 Math Refresher
2 Thu, 28.09.2017 Game Theory
3 Thu, 05.10.2017 Game Theory + P2P File Sharing
4 Thu, 12.10.2017 Auction Theory
5 Thu, 19.10.2017 Mechanism Design (Part 1)
6 Thu, 26.10.2017 Mechanism Design (Part 2)
7 Thu, 02.11.2017 Online Advertising Auctions
8 Thu, 09.11.2017 Linear Programming
9 Thu, 16.11.2017 Integer Programming
10 Thu, 23.11.2017 Combinatorial Auctions
11 Thu, 30.11.2017 Matching Markets
12 Thu, 07.12.2017 Computational Social Choice
13 Thu, 14.12.2017 Review/Practice Exam

Homework Assignments (tentative schedule)

Number Out Date Due Date Topic
01 Wed, 27.9.2017 Wed, 11.10.2017, 12:15 Game Theory (Theory)
02 Wed, 11.10.2017 Wed, 18.10.2017, 12:15 Auction Theory (Theory)
03 Wed, 18.10.2017 Wed, 1.11.2017, 12:15 Mechanism Design (Theory)
04 Wed, 1.11.2017 Wed, 8.11.2017, 12:15 Advertising Auctions (Programming)
05(a) Wed, 8.11.2017 Wed, 15.11.2017, 12:15 Linear Programming (Programming) [40%]
05(b) Wed, 15.11.2017 Wed, 22.11.2017, 12:15 Integer Programming (Programming) [60%]
06 Wed, 22.11.2017 Wed, 29.11.2017, 12:15 Combinatorial Auctions (Theory/Programming)
07(a) Wed, 29.11.2017 Wed, 6.12.2017, 12:15 Matching (Theory/Programming) [50%]
07(b) Wed, 6.12.2017

Wed, 13.12.2017, 12:15

Social Choice (Theory/Programming) [50%]

Teaching Format and Setup

  1. This course will be structured differently from most courses at IfI: For each lecture, there will be lecture notes (approx. 15-20 pages per lecture) that students must read before class to learn the new material at their own pace.
  2. Students must answer 4-5 short comprehension questions before every class to show they have completed the readings.
  3. During class, we will not go over all of the material from the lecture notes. Instead, lectures will be interactive, illustrating the concepts from the lecture notes, and students are expected to participate during class discussions.
  4. Every week, there will be a section (exercise session) to practice the concepts learned in the lecture. Participation in the exercise sessions will be very helpful to deepen the understanding of the material and to prepare for solving the homework exercises. However, attendance during the exercise sessions in not mandatory and will not be graded.
  5. There will be approximately 3-4 theoretical/mathematical homework exercises to deepen the understanding of the theoretical content of the course.
  6. There will be approximately 3-4 programming exercises where students need to apply the concepts learned in class.


No special prior knowledge is required. Students need to be proficient in math to solve the theoretical homework exercises, and they need to be able to program to solve the practical homework exercises. Taking the course Math-III before or while taking this course is recommended for BSc students, but not required. Furthermore, any background in microeconomics or game theory is helpful but not required.

Target Audience

Recommended for all BSc and MSc students with an interest in topics at the intersection of economics and computer science.

Teaching/Learning Goals

  1. Understand the importance of economic thinking in computational domains, and of computational thinking in economic domains.
  2. Be able to develop applicable models of complex Internet systems.
  3. Be able to analyze the behavior of systems that include people, computational agents as well as firms, and involve strategic behavior.
  4. Be able to solve both mathematical and conceptual problems involving such systems.
  5. Be able to write programs that implement strategic agents and mechanisms.

Examination + Grading

To pass the module, students need to obtain at least 50% of the points from the homework assignments and they need to pass the final exam. The final grade for the module will be determined as follows:

  1. Final Exam: 90% (December 20th, 2017 at 12:00-14:00)
  2. Comprehension questions: 10%

Weiterführende Informationen


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