Cooperative AI Foundation Courses

How to Do Research That Matters

Discover strategies for conducting impactful research in AI safety and cooperation, focusing on multi-agent systems and responsible technology development.

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

Unsupervised Environment Design

Explore automatic generation of environments for training RL agents, from GenIE to Unsupervised Environment Design, bridging classical decision theory and deep learning.

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

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

Game Theory and Machine Learning for Addressing Societal Challenges

Explore game theory and machine learning applications for societal challenges. Learn from Fei Fang's expertise in AI, multi-agent systems, and their impact on security, sustainability, and mobility.

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

Computational Social Choice and AI Value Learning

Explore computational social choice and AI value learning, focusing on misspecification in RLHF, model interpretability, and foundation model capability evaluations.

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

Neuro-Symbolic Methods for Open-Ended Cooperative AI

Explore neuro-symbolic approaches for developing open-ended cooperative AI systems, bridging multi-agent reinforcement learning with sociology and economics.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Normative Intelligence - Cooperative AI Summer School 2024

Explore normative intelligence and its implications for AI governance, safety, and societal impact with insights from law, economics, and technology.

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

Achieving Cooperative Outcomes in Mixed Settings

Explore strategies for achieving cooperative outcomes in diverse environments. Learn from Nisarg Shah's expertise in fairness, efficiency, and algorithmic decision-making affecting humans.

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

Distributed Computing Meets Game Theory

Explore the intersection of distributed computing and game theory, examining their synergies and applications in multi-agent systems and decision-making processes.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Concordia Contest 2024 - Basic Agent Development Tutorial

Develop cooperative AI agents for text-based environments using the Concordia framework. Advance language model intelligence in open-ended worlds similar to tabletop RPGs.

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

Learning to Cooperate and Compete via Self Play

Explore AI strategies for cooperation and competition through self-play, featuring insights from poker AI breakthroughs and their broader implications.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video

A Foundation Model for Cooperative AI

Explore a foundation model for Cooperative AI, bridging multi-agent reinforcement learning with sociology and economics for enhanced algorithmic partnerships.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

RLHF: How to Learn from Human Feedback with Reinforcement Learning

Explore reinforcement learning techniques for incorporating human feedback in AI systems, enhancing multi-agent and human-AI interactions in social contexts.

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

Fostering Cooperation via Fairness in AI Systems

Explore fairness in AI decision-making, addressing efficiency, elicitation, and incentives. Learn theoretical foundations for fairness in voting, resource allocation, and machine learning.

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

Foundations of Cooperative AI

Explore the foundations of Cooperative AI with Prof. Vincent Conitzer, covering key concepts and applications in this emerging field of artificial intelligence research.

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