Course Identification

Algorithms, Games, and Economics
20254232

Lecturers and Teaching Assistants

Prof. Shahar Dobzinski
Ariel Shaulker

Course Schedule and Location

2025
Second Semester
Monday, 09:15 - 11:00, Ziskind, Rm 1
24/03/2025
30/06/2025

Field of Study, Course Type and Credit Points

Mathematics and Computer Science: Lecture; Elective; Regular; 3.00 points

Comments

N/A

Prerequisites

Basic knowledge of algorithms, complexity, and probability. Familiarity with game theory and economics will not be assumed.

Restrictions

50

Language of Instruction

English

Attendance and participation

Expected and Recommended

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

40%
60%

Evaluation Type

Take-home exam

Scheduled date 1

N/A
N/A
-
N/A

Estimated Weekly Independent Workload (in hours)

5

Syllabus

In this course, we will explore Algorithmic Game Theory, a field at the intersection of computer science, game theory, and economics. We will study how to design algorithms that perform well even in environments where agents act selfishly. Examples of such environments include auctions, resource allocation problems, and emerging cryptocurrency markets like Bitcoin. Additionally, we will apply algorithmic perspectives to analyze the performance of various economic markets. Toward the end of the course, we will delve into recent research directions, such as using algorithmic lenses to analyze problems from behavioral economics.

Learning Outcomes

Upon successful completion of this course students should be able to:

  1. Demonstrate familiarity with the basic notions of algorithmic game theory.
  2. Understand some current important research directions in the field.

Reading List

N/A.

Website

N/A