Mechanism Design for Data Science (097245) +
Social Computing Models (097246)
Prof. Moshe Tennenholtz (first name + last name initial @ ie.technion.ac.il)
Inspired by the emergence of Internet commerce and advertising as well as social networks, recent years have been flowering in establishing connections between computer science to the social sciences, and in particular economics. Some of the foundational work has been carried out in the theoretical CS community and some by the AI community. Course 097245 provides the fundamental models one needs to know in order to understand the foundations of work on these topics. It is a basic course as it is built only on familiarity with calculus and linear algebra, probability, and graph algorithms. It is however a relatively advanced course as it will focus on foundations rather than on general introduction, and requires mathematical maturity. The topics studied are centered around preparation for a research project carried out at end of the course. The research project requires high mathematical/algorithmic maturity and abilities. Topics to be covered include an introduction to game theory, congestion and network games, auctions, facility location games, sponsored search, preference aggregation, information design, approximate mechanism design without money, and voting in networks.
Course 097246, social computing models, is complementary to the Mechanism
Design for Data Science (097245), although 097245 is not a formal pre-requisite.
While 097245 provides related fundamental game theoretic and economic models, essential to the CS /AI and economics/GT interplay, 097246 considers the agent, mediator, and axiomatic models perspectives, as well the intersection with distributed computing, social design and reinforcement learning, introduced as part of that interplay. While here again the formal course requirements are calculus and linear algebra, probability, and graph algorithms, active engagement in classes of 097245, or especially high mathematical maturity and proven mathematical abilities are essential. The course consists of lectures, self reading and seminars presented by students, and a research project.