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Cooperative AI
Thore Graepel · Dario Amodei · Vincent Conitzer · Allan Dafoe · Gillian Hadfield · Eric Horvitz · Sarit Kraus · Kate Larson · Yoram Bachrach

Sat Dec 12 05:20 AM -- 12:55 PM (PST) @ None
Event URL: https://www.cooperativeai.com/ »


Problems of cooperation—in which agents seek ways to jointly improve their welfare—are ubiquitous and important. They can be found at all scales ranging from our daily routines—such as highway driving, communication via shared language, division of labor, and work collaborations—to our global challenges—such as disarmament, climate change, global commerce, and pandemic preparedness. Arguably, the success of the human species is rooted in our ability to cooperate, in our social intelligence and skills. Since machines powered by artificial intelligence and machine learning are playing an ever greater role in our lives, it will be important to equip them with the skills necessary to cooperate and to foster cooperation.

We see an opportunity for the field of AI, and particularly machine learning, to explicitly focus effort on this class of problems which we term Cooperative AI. The goal of this research would be to study the many aspects of the problem of cooperation, and innovate in AI to contribute to solving these problems. Central questions include how to build machine agents with the capabilities needed for cooperation, and how advances in machine learning can help foster cooperation in populations of agents (of machines and/or humans), such as through improved mechanism design and mediation.

Research could be organized around key capabilities necessary for cooperation, including: understanding other agents, communicating with other agents, constructing cooperative commitments, and devising and negotiating suitable bargains and institutions. Since artificial agents will often act on behalf of particular humans and in ways that are consequential for humans, this research will need to consider how machines can adequately learn human preferences, and how best to integrate human norms and ethics into cooperative arrangements.

We are planning to bring together scholars from diverse backgrounds to discuss how AI research can contribute to the field of cooperation.

Call for Papers
We invite high-quality paper submissions on the following topics (broadly construed, this is not an exhaustive list):

-Multi-agent learning
-Agent cooperation
-Agent communication
-Resolving commitment problems
-Agent societies, organizations and institutions
-Trust and reputation
-Theory of mind and peer modelling
-Markets, mechanism design and and economics based cooperation
-Negotiation and bargaining agents
-Team formation problems

Accepted papers will be presented during joint virtual poster sessions and be made publicly available as non archival reports, allowing future submissions to archival conferences or journals.

Submissions should be up to eight pages excluding references, acknowledgements, and supplementary material, and should follow NeurIPS format. The review process will be double-blind.

Paper submissions: https://easychair.org/my/conference?conf=coopai2020#

Author Information

Thore Graepel (DeepMind)
Dario Amodei (OpenAI)
Vincent Conitzer (Duke University)

Vincent Conitzer is the Kimberly J. Jenkins University Professor of New Technologies and Professor of Computer Science, Professor of Economics, and Professor of Philosophy at Duke University. He received Ph.D. (2006) and M.S. (2003) degrees in Computer Science from Carnegie Mellon University, and an A.B. (2001) degree in Applied Mathematics from Harvard University. Conitzer works on artificial intelligence (AI). Much of his work has focused on AI and game theory, for example designing algorithms for the optimal strategic placement of defensive resources. More recently, he has started to work on AI and ethics: how should we determine the objectives that AI systems pursue, when these objectives have complex effects on various stakeholders? Conitzer has received the Social Choice and Welfare Prize, a Presidential Early Career Award for Scientists and Engineers (PECASE), the IJCAI Computers and Thought Award, an NSF CAREER award, the inaugural Victor Lesser dissertation award, an honorable mention for the ACM dissertation award, and several awards for papers and service at the AAAI and AAMAS conferences. He has also been named a Guggenheim Fellow, a Sloan Fellow, a Kavli Fellow, a Bass Fellow, an ACM Fellow, a AAAI Fellow, and one of AI's Ten to Watch. He has served as program and/or general chair of the AAAI, AAMAS, AIES, COMSOC, and EC conferences. Conitzer and Preston McAfee were the founding Editors-in-Chief of the ACM Transactions on Economics and Computation (TEAC).

Allan Dafoe (University of Oxford)
Gillian Hadfield (University of Toronto, Vector Institute, and OpenAI)
Eric Horvitz (Microsoft Research)
Sarit Kraus (Bar-Ilan University)
Kate Larson (DeepMind, University of Waterloo)
Yoram Bachrach (Google DeepMind)

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