Title

Learning to Decide: from no-regret learning to strategic games

Abstract

Learning to make effective decisions in dynamic and uncertain environments lies at the heart of both machine learning and game theory. This talk presents the conceptual and algorithmic connections between no-regret learning—a foundational framework in online decision-making—and strategic games, where multiple agents interact with potentially conflicting interests. We demonstrate how no-regret algorithms lead to equilibria in repeated games, providing a bridge between individual learning dynamics and collective strategic behavior.

----------------

Everyone is welcome!

There will be refreshments after the lecture.