Events

The first Cooperative AI workshop plans to bring together scholars from diverse backgrounds to discuss how AI research can contribute to the field of cooperation.

The second Cooperative AI workshop is focused on how to incentivize cooperation in AI systems, and how to implement effective coordination given these incentives.

The Cooperative AI Summer School is an advanced programme for early-career professionals already working in or studying cooperative AI. Over five intensive days, participants will attend talks from leading researchers and work on collaborative projects tackling real cooperative AI challenges.

The Cooperative AI Summer School is designed to provide students and early-career professionals in AI, computer science and related disciplines, such as sociology and economics, with a firm grounding in the emerging field of cooperative AI.

The Cooperative AI Summer School is designed to provide students and early-career professionals in AI, computer science, and related disciplines with a firm grounding in the emerging field of cooperative AI.

The Cooperative AI Summer School is designed to provide students and early-career professionals in AI, computer science, and related disciplines with a firm grounding in the emerging field of cooperative AI.

In collaboration with colleagues from Google DeepMind, MIT, UC Berkeley, and UCL, the Cooperative AI Foundation is excited to present the Concordia Contest as part of NeurIPS 2024. This contest challenges participants to advance the cooperative intelligence of language model (LM) agents in rich, text-based environments, based on the recently released Concordia framework which uses language models to create open-ended worlds similar to tabletop role-playing games.

In collaboration with colleagues from Google DeepMind and MIT, the Cooperative AI Foundation is running a major cooperative AI contest as part of NeurIPS 2023. We challenge you to push the boundaries of multi-agent reinforcement learning by developing agents that can solve diverse mixed-motive cooperation problems from the Melting Pot environment suite.