Multistage Games: Extensive Form and Feedback Strategies

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

Covers bidding strategies, Game Theory, Nash equilibrium, system security, ancillary services, and market power in power systems.

Covers the formulation of optimization programs for minimizing piecewise linear cost functions.

Covers the modelling and optimization of energy systems, focusing on solving optimization problems with constraints and variables.

Covers semi-definite programming and optimization over positive semidefinite cones.

Explores the historical perspective and development of the AlphaGo algorithm, focusing on machine learning and game strategies.

Covers optimization methods without constraints, including gradient and line search in the quadratic case.

Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.

Delves into learning dynamics in games, exploring chaos, limit cycles, and the interplay between convergence and chaos.

Introduces the Simplex algorithm for solving flow problems and handling negative cost cycles.

Explains the SIMPLEX method for solving linear programs and optimizing the solution through basis variable manipulation.

Explores challenges in control, safety, and coordination for autonomous systems like autonomous cars, focusing on safe learning and Nash equilibria.

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