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Connect Four: Game Theory Approach
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Related lectures (31)
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Heuristic Optimization Methods
Explores heuristic optimization methods to find the global optimum efficiently.
Introduction to Game Theory
Covers game theory fundamentals, Nash equilibrium, and strategic interactions in multi-agent systems.
Multistage Games: Extensive Form and Feedback Strategies
Explores multistage games, focusing on extensive form and feedback strategies, including Nash equilibria and backward induction methods.
Chemical Reaction Optimization: Multi-Task Learning
Explores multi-task learning for accelerated chemical reaction optimization, showcasing challenges, automated workflows, and optimization algorithms.
Markov Chains and Algorithm Applications
Covers the application of Markov chains and algorithms for function optimization and graph colorings.
Motor control systems
Explores motor control systems, covering algorithms, sensor integration, and practical applications in robotics and automation.
Optimisation in Energy Systems
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
Potential Games: Best-Response Dynamics and Equilibria
Covers potential games, their properties, and the convergence of best-response dynamics to Nash equilibria.
Understanding Generalization: Implicit Bias & Optimization
Explores the trade-off between complexity and risk in machine learning models, the benefits of overparametrization, and the implicit bias of optimization algorithms.
Zero-Sum Games: Concepts and Applications
Covers zero-sum games, focusing on Nash equilibria, security strategies, and their applications in various scenarios.
