Recent years have witnessed significant advances in reinforcement learning (RL), which
has registered tremendous success in solving various sequential decision-making problems …

Publisher Summary This chapter provides an overview of the latest state of the art of
methods for numerical computation of Nash equilibria—and refinements of Nash equilibria …

Poker is a family of games that exhibit imperfect information, where players do not have full
knowledge of past events. Whereas many perfect-information games have been solved (eg …

Planning algorithms are impacting technical disciplines and industries around the world,
including robotics, computer-aided design, manufacturing, computer graphics, aerospace …

This work studies an algorithm, which we call magnetic mirror descent, that is inspired by
mirror descent and the non-Euclidean proximal gradient algorithm. Our contribution is …

Most existing results about last-iterate convergence of learning dynamics are limited to two-
player zero-sum games, and only apply under rigid assumptions about what dynamics the …

In multiagent systems, strategic settings are often analyzed under the assumption that the
players choose their strategies simultaneously. However, this model is not always realistic …

Fictitious play is a popular game-theoretic model of learning in games. However, it has
received little attention in practical applications to large problems. This paper introduces two …

Sequential decision making is a fundamental task faced by any intelligent agent in an
extended interaction with its environment; it is the act of answering the question" What …

We prove the existence of ε-Nash equilibrium strategies with support logarithmic in the
number of pure strategies. We also show that the payoffs to all players in any (exact) Nash …