Lectures related to Real World Games: Negotiation Strategies

Covers game theory fundamentals, Nash equilibrium, and strategic interactions in multi-agent systems.

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.

Markov Games: Concepts and Applications in Reinforcement Learning

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

Potential Games: Best-Response Dynamics and Equilibria

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

Game Theory: Stackelberg and Backward Induction

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

Zero-Sum Games: Concepts and Applications

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

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: Decision Making in Interdependent Environments

Explores game theory, decision-making in interdependent environments, equilibrium concepts, and economic applications in management.

Dynamic Games: Theory and Applications

Covers dynamic games, focusing on their structure, applications, and the transition from tree to loop models.

Potential Games: Best Response Dynamics and Nash Equilibria

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

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.

Decisions under Risk and Uncertainty: Behavioral Economics Insights

Delves into decision-making under risk, bounded rationality, prospect theory, and framing, with insights from behavioral economics.

Dynamic Games: Backward Induction and Nash Equilibria

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

Equilibrium State Prices Determination

Explains the determination of equilibrium state prices in asset pricing through consumption market clearing and budget constraints.

Safe Learning for Autonomous Systems

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

Uncertainty Analysis in LCA

Explores uncertainty analysis in Life Cycle Assessment, covering sensitivity, probability functions, parameter estimation, pedigree approach, and uncertainty propagation.

Propagation of Uncertainty: Probability Density Function

Covers the propagation of uncertainty through the generation of probability density functions.

Beyond equilibrium: A dynamical systems approach to learning in games

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

Imperfect Competition: Cartels and Oligopoly

Explores imperfect competition, cartels, and oligopoly dynamics in markets, analyzing pricing strategies and market outcomes.