Nash Equilibrium Courses and Certifications

Dave Churchill

Introduction to Artificial Intelligence - 2022

Explore AI fundamentals through algorithmic techniques, search methods, game theory, and reinforcement learning with hands-on game-based assignments.

• YouTube
• 1 day 51 minutes
• On-Demand
• Free Video

Dave Churchill

Introduction to Artificial Intelligence (2021-09)

Explore AI fundamentals through algorithmic techniques, search methods, game theory, evolutionary computing, and reinforcement learning with hands-on game applications.

• YouTube
• 1 day 3 hours 43 minutes
• On-Demand
• Free Video

Complexity Explorer

Game Theory Tutorial - Static Games

Master strategic decision-making through Nash equilibrium, dominant strategies, mixed strategies, and Bayesian games with real-world applications in cybersecurity and commons dilemmas.

• YouTube
• 1 hour 47 minutes
• On-Demand
• Free Video

NPTEL;  IIT Bombay

Game Theory

The aim of this course is to introduce the following topics at a basic level: combinatorial games, zero-sum games, non-zero sum games and cooperative games. At the end of the course, the student should be able to • Model and analyse conflicting situation…

• YouTube
• 20 hours
• On-Demand
• Free Video

How Can We Understand Our Complex Economy?

Explore complex systems approach to economics, blending insights from physical and natural sciences to predict and mitigate economic crises, offering a new perspective on global financial challenges.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

International Mathematical Union

Independent Learning Dynamics for Stochastic Games - Where Game Theory Meets

Explore independent learning dynamics in stochastic games, bridging game theory and reinforcement learning. Discover convergent algorithms for multi-agent scenarios in dynamic environments.

• YouTube
• 46 minutes
• On-Demand
• Free Video

International Centre for Theoretical Sciences

Analysis of Mean-Field Games - Lecture 1

Explore static mean-field games, Nash equilibria, and convergence theorems in large symmetric systems. Learn key concepts and proofs in this advanced applied probability lecture.

• YouTube
• 1 hour
• On-Demand
• Free Video

Simons Institute

A Variational Inequality Framework for Network Games

Explore a variational inequality framework for network games, covering game theory connections, Jacobian properties, and sufficient conditions for Nash equilibria in symmetric networks.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Simons Institute

Learning Decentralized Policies in Multiagent Systems - How to Learn Efficiently

Explore decentralized policy learning in multiagent systems, focusing on scalable actor-critic methods, network structures, and performance characterization using stochastic game frameworks.

• YouTube
• 51 minutes
• On-Demand
• Free Video

Simons Institute

V-Learning - Simple, Efficient, Decentralized Algorithm for Multiagent RL

Explore efficient decentralized algorithms for multiagent reinforcement learning, focusing on V-learning's ability to overcome challenges in joint action spaces and achieve Nash equilibria.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Simons Institute

Multi-Agent Reinforcement Learning - Part I

Explore multi-agent reinforcement learning, covering game theory, interaction protocols, and Nash equilibrium. Gain insights into challenges and formulations in this emerging field.

• YouTube
• 57 minutes
• On-Demand
• Free Video

Inside Livermore Lab

Competitive Physics Informed Networks - Overcoming Limitations in PDE Solutions

Explore competitive physics-informed neural networks for solving PDEs with unprecedented accuracy. Learn about adversarial approaches and zero-sum games to achieve single-precision accuracy in numerical simulations.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Dave Churchill

Introduction to Artificial Intelligence: Game Theory - Lecture 8 (Part 1)

Explore game theory fundamentals, strategic decision-making, and AI applications in competitive environments. Gain insights into rational agent behavior and equilibrium concepts.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Cooperative AI Foundation

Self-Play in Artificial Intelligence - Lecture by Noam Brown

Explore advanced AI techniques in imperfect-information games, focusing on self-play algorithms and their applications in poker and beyond.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Discover AI

Strategic Deviations in Multi-Agent Imitation Learning: From Value Optimization to Regret Analysis

Delve into the complex dynamics of multi-agent AI systems, exploring strategic deviations, regret gaps, and equilibrium concepts in imitation learning through practical applications and mathematical frameworks.

• YouTube
• 38 minutes
• On-Demand
• Free Video