Richard Everett

Orcid: 0000-0002-9404-6338

Affiliations:
  • DeepMind Technologies Limite, London, United Kingdom


According to our database1, Richard Everett authored at least 19 papers between 2016 and 2023.

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Bibliography

2023
Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas.
CoRR, 2023

2022
Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering.
CoRR, 2022

Learning Robust Real-Time Cultural Transmission without Human Data.
CoRR, 2022

Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria.
CoRR, 2022

Developing, evaluating and scaling learning agents in multi-agent environments.
AI Commun., 2022

Quantifying the effects of environment and population diversity in multi-agent reinforcement learning.
Auton. Agents Multi Agent Syst., 2022

Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

D3C: Reducing the Price of Anarchy in Multi-Agent Learning.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Quantifying environment and population diversity in multi-agent reinforcement learning.
CoRR, 2021

Collaborating with Humans without Human Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Modelling Cooperation in Network Games with Spatio-Temporal Complexity.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020
Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences.
CoRR, 2020

Negotiating team formation using deep reinforcement learning.
Artif. Intell., 2020

Bounds and dynamics for empirical game theoretic analysis.
Auton. Agents Multi Agent Syst., 2020

Learning to Play No-Press Diplomacy with Best Response Policy Iteration.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Learning Against Non-Stationary Agents with Opponent Modelling and Deep Reinforcement Learning.
Proceedings of the 2018 AAAI Spring Symposia, 2018

2016
The anatomy of online deception: what makes automated text convincing?
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016


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