Beyond equilibrium: A dynamical systems approach to learning in games

Related lectures (31)

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Covers game theory fundamentals, Nash equilibrium, and strategic interactions in multi-agent systems.

Discusses Stackelberg games and backward induction, illustrating game theory concepts through examples and applications in real-world scenarios.

Covers Markov games, their dynamics, equilibria, and applications in reinforcement learning.

Explores multistage games, focusing on extensive form and feedback strategies, including Nash equilibria and backward induction methods.

Covers zero-sum games, focusing on Nash equilibria, security strategies, and their applications in various scenarios.

Covers potential games, their properties, and the convergence of best-response dynamics to Nash equilibria.

Covers the basics of static games and introduces key game theory concepts, including the Prisoner's Dilemma and Nash Equilibrium.

Covers learning dynamics in finite action games and explores various types of equilibria, including correlated and coarse correlated equilibria.

Delves into real-world games, negotiation strategies, and optimal agreements beyond Nash equilibrium.

Explores challenges in control, safety, and coordination for autonomous systems like autonomous cars, focusing on safe learning and Nash equilibria.