Cooperative AI Contest

Concordia Contest 2024

Aims and Focus
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.

The field of cooperative AI focuses on enhancing the cooperative intelligence of AI systems. We define an agent's cooperative intelligence as its ability to achieve its goals in ways that also promote social welfare, across diverse environments and partners. The Concordia Contest presents a variety of scenarios where agents must engage in cooperative behaviour to attain high returns. These scenarios test skills such as promise-keeping, negotiation, reciprocity, reputation, partner choice, compromise, and sanctioning.

The contest is based on the recently proposed Concordia framework for interactions between LM agents. Participants will be required to design and submit a single Concordia agent to be evaluated across multiple scenarios. These agents will interact with both familiar and unfamiliar populations of agents in the test scenarios. The contest will rank submissions based on average returns across scenarios in different modes, such as self-play and cross-play.

The contest timeline includes a development phase for iterative improvement and a final test phase for official scoring. The contest is hosted in collaboration with colleagues from Google DeepMind, MIT, UC Berkeley, and UCL, offering $10,000 in prizes to top performers. Top performers will also be invited to co-author a report on the contest, to be submitted to the NeurIPS 2025 Datasets & Benchmarks track. Further details regarding the rules of the contest and information about how to enter can be found here.

The combination of mixed-motive scenarios, generalisation testing, and complex interactions makes the Concordia Contest a uniquely challenging and relevant benchmark for cooperative AI. By hosting this contest at NeurIPS 2024, we aim to drive progress in cooperative AI and multi-agent learning, establish consensus on metrics for cooperation, and engage the wider research community. We believe that developing cooperative intelligence in artificial agents can lead to technologies that foster fairer and more flourishing societies.

In keeping with this motivation, we are committed to making this contest as accessible and inclusive as possible, by offering $10,000 in travel grants, and $50,000 in compute credits to support participants from under-resourced and underrepresented groups. You can apply for compute credits here. The deadline to apply is October 5, and we will notifiy successful applicants shortly afterwards.

Please contact us if you have any further questions about taking part. Good luck!

Key Dates

September 18: Development phase begins

October 5: Compute credits application deadline

October 31: Development phase ends
November 1: Evaluation and review phase begins
November 20: Finalists notified
December 3: Deadline for submission of entry details
December 9-15: NeurIPS conference and winners announced

Organizers

Chandler Smith
Research Engineer, Cooperative AI Foundation
Research Scholar, MATS
Rakshit Trivedi
Postdoctoral Associate, MIT
Jesse Clifton
Research Analyst, Cooperative AI Foundation
Lead Researcher, Center on Long-Term Risk
Lewis Hammond
Research Director, Cooperative AI Foundation
DPhil Candidate, University of Oxford
Akbir Khan
Researcher, Anthropic
PhD Student, UCL
Marwa Abdulhai
PhD Student, UC Berkeley
Alexander Vezhnevets
Staff Research Scientist, Google DeepMind
John Agapiou
Staff Research Engineer, Google DeepMind
Edgar Duéñez Guzmán
Staff Research Engineer, Google DeepMind
Jayd Matyas
Research Environment Designer, Google DeepMind
Danny Karmon
Staff Research and Engineering Manager, Google DeepMind
Oliver Slumbers
PhD Student, UCL
Minsuk Chang
Research Scientist, Google DeepMind
Joel Leibo
Senior Staff Research Scientist, Google DeepMind

Advisory Board

Sergey Levine
Associate Professor, UC Berkeley
Natasha Jaques
Assistant Professor, University of Washington
Senior Research Scientist, Google DeepMind
Tim Baarslag
Senior Researcher, Centrum Wiskunde & Informatica
Professor, Eindhoven University of Technology
Associate Professor, Utrecht University
Dylan Hadfield-Menell
Assistant Professor, MIT
José Hernández-Orallo
Professor, Universitat Politècnica de València

Sponsors

Cooperative AI Foundation
Google DeepMind