20972 - ADVANCED MICROECONOMICS FOR COMPUTER SCIENCE
Department of Economics
Course taught in English
Go to class group/s: 31
CLMG (6 credits - I sem. - OP | SECS-P/01) - M (6 credits - I sem. - OP | SECS-P/01) - IM (6 credits - I sem. - OP | SECS-P/01) - MM (6 credits - I sem. - OP | SECS-P/01) - AFC (6 credits - I sem. - OP | SECS-P/01) - CLELI (6 credits - I sem. - OP | SECS-P/01) - ACME (6 credits - I sem. - OP | SECS-P/01) - DES-ESS (6 credits - I sem. - OP | SECS-P/01) - EMIT (6 credits - I sem. - OP | SECS-P/01) - GIO (6 credits - I sem. - OP | SECS-P/01) - DSBA (6 credits - I sem. - OP | SECS-P/01) - PPA (6 credits - I sem. - OP | SECS-P/01) - FIN (6 credits - I sem. - OP | SECS-P/01) - AI (6 credits - I sem. - OP | SECS-P/01)
Course Director:
MARTINO BANCHIO
MARTINO BANCHIO
Suggested background knowledge
To provide a solid foundation in microeconomic theory and its relevance to computer science.
Mission & Content Summary
MISSION
Course Description:
The course explores topics at the intersection of advanced microeconomics and computer science. The course objectives are:
1. To provide a solid foundation in microeconomic theory and its relevance to computer science.
2. To develop analytical and critical thinking skills for modeling and solving problems involving strategic agents.
3. To expose students to current research topics in microeconomic research with a focus on relevant applications in the computer sciences.
The course covers topics such as preferences, utility, demand, supply, equilibrium, market design, game theory, mechanism design, social choice, and welfare. The course emphasizes the algorithmic and computational aspects of these topics, as well as their applications to, such as e-commerce, online platforms, social networks, and artificial intelligence. The course also explores some of the limitations and challenges of applying microeconomic models to real-world scenarios.
CONTENT SUMMARY
1. Introduction
2. Preferences and Utility
3. Tractable Models of Single-Agent Decisions
4. Algorithmic Game Theory
5. Algorithmic Mechanism Design
6. Network economics
Other Possible Topics
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
To provide a solid foundation in microeconomic theory and its relevance to computer science.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
To develop analytical and critical thinking skills for modeling and solving problems involving strategic agents.
To expose students to current research topics in microeconomic research with a focus on relevant applications in the computer sciences
Teaching methods
- Lectures
DETAILS
Face to face lectures
Assessment methods
| Continuous assessment | Partial exams | General exam | |
|---|---|---|---|
|
x | x |
ATTENDING STUDENTS
Class Participation 30%, Midterm 30%, Final Exam 40%. Class participation consists of active engagement in discussions, and demonstrated critical thinking and ability to synthesize information as it is processed. Midterm and Final exams are meant to measure the student's understanding of concepts, their ability to apply them and their problem-solving skills.
NOT ATTENDING STUDENTS
Class Participation 30%, Midterm 30%, Final Exam 40%. Class participation consists of active engagement in discussions, and demonstrated critical thinking and ability to synthesize information as it is processed. Midterm and Final exams are meant to measure the student's understanding of concepts, their ability to apply them and their problem-solving skills.
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
The course will largely be based off of the book "Algorithmic Game Theory" edited by Nisan, Roughgarder, Tardos and Vazirani, which can be downloaded at the following link: https://www.cs.cmu.edu/~sandholm/cs15-892F13/algorithmic-game-theory.pdf. Other material may be provided at the instructor's discretion.
Last change 29/05/2024 09:21