Learning and Incentives | Learning and Games Boot Camp

Classically, the outcome of a learning algorithm is considered in isolation from the effects that it may have on the process that generates the data or the party who is interested in learning. In today's world, increasing numbers of people and organizations interact with learning systems, making it necessary to consider these effects. This tutorial by Nika Haghtalab (UC Berkeley) from our Learning and Games Boot Camp in January 2022 covers the mathematical foundations for addressing learning and learnability in the presence of economic and social forces.