Solving Connect Four: A-B Pruning and Monte-Carlo Tree Search

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Markov Games: Concepts and Applications in Reinforcement Learning

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

Verlet and Gear Algorithms

Discusses the Verlet and Gear algorithms for harmonic oscillators, emphasizing stability and performance evaluation.

Solving Parity Games in Practice

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Game Theory: Stackelberg and Backward Induction

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

Deliberative Agents: Planning and Strategies

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

Separating Hyperplanes: Theory and Applications

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

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 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.