ME-429: Multiagent decision-making and control

Lectures in this course (9)

Covers convex games, their equilibria, and applications in various fields such as traffic and electricity markets.

Covers dynamic games, focusing on their structure, applications, and the transition from tree to loop models.

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

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

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.

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

Covers dynamic games, focusing on backward induction and finding Nash equilibria in two-player scenarios.

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