Solving Connect Four: Game Theory Strategies

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Markov Games: Concepts and Applications in Reinforcement Learning

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

Separating Hyperplanes: Theory and Applications

Explores separating hyperplanes for two sets X and Y, discussing conditions for separation and implications of convexity.

Potential Games: Best-Response Dynamics and Equilibria

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

Static Games: Introduction to Game Theory Concepts

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

Zero-Sum Games: Concepts and Applications

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

Multistage Games: Extensive Form and Feedback Strategies

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

Game Theory Applications: Project Proposals and Examples

Provides guidance on project proposals in game theory, showcasing past examples and emphasizing problem formulation and mathematical modeling.

Potential Games: Best Response Dynamics and Nash Equilibria

Covers potential games, best response dynamics, and the convergence to Nash equilibria.

Deliberative Agents: Planning and Strategies

Covers planning with adversaries, heuristic search algorithms, and strategies for games with chance, emphasizing the significance of deliberative agents.

Dynamic Games: Backward Induction and Nash Equilibria

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