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CS 598 RM - Special Topics - Algorithmic Game Theory

Campus: Urbana-Champaign


Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

Special Instructions:

All class meetings will be online and synchronous. Description: The field of game theory analyses organizations/settings where rational selfish agents interact, like voting, (spectrum) auctions, social networks, mediations, and bargaining. For such organizations, it aims to study their stable outcomes, designing rules to achieve good stable outcomes, welfare loss, dynamics, etc.. Algorithmic game theory studies computational aspects of each of these aspects, e.g., how fast we can compute the solutions. The goal of this course is to expose students to three main objectives of algorithmic game theory: (i) analysis and algorithms for stable outcomes (games, equilibria, and computation), (ii) efficient rule design to achieve good stable outcomes (mechanism design and fair-division), and (iii) analysis of welfare loss and dynamics (selfish routing and price-of-anarchy). A research/survey project will be a major part of this course. Being a theory course, CS 473 or equivalent is recommend

Option 1

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 4

Term(s): Fall


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