Richard Everett

DeepMind (United Kingdom) — United Kingdom

Environmental Science · Physical Sciences

27h-index2.6kcitations121works0.02yr avg
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Research Topics

Fire effects on ecosystems(24), Rangeland and Wildlife Management(23), Ecology and Vegetation Dynamics Studies(19), Forest ecology and management(16), Reinforcement Learning in Robotics(13)

Publications121 total

Learning few-shot imitation as cultural transmission
Nature Communications·2023· 12 citedOpen Access
Scaffolding cooperation in human groups with deep reinforcement learning
Nature Human Behaviour·2023· 22 citedOpen Access
Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas
arXiv (Cornell University)·2023· 1 citedOpen Access
Using the Veil of Ignorance to align AI systems with principles of justice
Proceedings of the National Academy of Sciences·2023· 35 citedOpen Access
Scaffolding cooperation in human groups with deep reinforcement learning
2022· 5 citedOpen Access
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments
arXiv (Cornell University)·2022Open Access
Developing, evaluating and scaling learning agents in multi-agent environments
AI Communications·2022· 1 cited
Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering
arXiv (Cornell University)·2022Open Access
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent
2022· 2 citedOpen Access
D3C: Reducing the Price of Anarchy in Multi-Agent Learning
2022· 3 citedOpen Access
Quantifying the effects of environment and population diversity in multi-agent reinforcement learning
Autonomous Agents and Multi-Agent Systems·2022· 17 citedOpen Access
Learning Robust Real-Time Cultural Transmission without Human Data
arXiv (Cornell University)·2022· 2 citedOpen Access
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria
arXiv (Cornell University)·2022· 1 citedOpen Access
Collaborating with Humans without Human Data
arXiv (Cornell University)·2021· 3 citedOpen Access
Modelling Cooperation in Network Games with Spatio-Temporal Complexity
2021· 2 citedOpen Access
Quantifying environment and population diversity in multi-agent reinforcement learning
arXiv (Cornell University)·2021· 2 citedOpen Access
Quantifying the effects of environment and population diversity in multi-agent reinforcement learning
arXiv (Cornell University)·2021Open Access
Silly rules enhance learning of compliance and enforcement behavior in artificial agents
2021
Negotiating Team Formation Using Deep Reinforcement Learning
arXiv (Cornell University)·2020Open Access
Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences
arXiv (Cornell University)·2020· 11 citedOpen Access
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Frequent Co-authors

Richard Schellhaas(5), D. Zabowski(5), George Scherer(5), F. Martin Wilt(5), Glenn C. Miller(5), Paul F. Hessburg(4), Don Spurbeck(4), Pete Ohlson(4), John F. Lehmkuhl(4), Roger D. Ottmar(4), David Keenum(3), Susan Koniak(3), Edward Hughes(3), Joel Z. Leibo(3), Marc Lanctot(3), Thore Graepel(3), Kevin R. McKee(3), Steven H. Sharrow(3), Vinod P. Shah(2), Jerome P. Skelly(2)