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Related lectures (8)
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Game Theory: Stackelberg and Backward Induction
Discusses Stackelberg games and backward induction, illustrating game theory concepts through examples and applications in real-world scenarios.
Introduction to Game Theory
Covers game theory fundamentals, Nash equilibrium, and strategic interactions in multi-agent systems.
Markov Games: Concepts and Applications in Reinforcement Learning
Covers Markov games, their dynamics, equilibria, and applications in reinforcement learning.
Multistage Games: Extensive Form and Feedback Strategies
Explores multistage games, focusing on extensive form and feedback strategies, including Nash equilibria and backward induction methods.
Potential Games: Best-Response Dynamics and Equilibria
Covers potential games, their properties, and the convergence of best-response dynamics to Nash equilibria.
Dynamic Games: Backward Induction and Nash Equilibria
Covers dynamic games, focusing on backward induction and finding Nash equilibria in two-player scenarios.
Game Theory: Learning in Finite Action Games
Covers learning dynamics in finite action games and explores various types of equilibria, including correlated and coarse correlated equilibria.
Convex Games: Applications and Equilibria
Covers convex games, their equilibria, and applications in various fields such as traffic and electricity markets.
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