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Richard Everett 0001
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- affiliation: DeepMind Technologies Limite, London, United Kingdom
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2020 – today
- 2023
- [i14]Udari Madhushani, Kevin R. McKee, John P. Agapiou, Joel Z. Leibo, Richard Everett, Thomas W. Anthony, Edward Hughes, Karl Tuyls, Edgar A. Duéñez-Guzmán
:
Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas. CoRR abs/2305.00768 (2023) - 2022
- [j4]Kevin R. McKee
Quantifying the effects of environment and population diversity in multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. 36(1): 21 (2022) - [j3]Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán
Developing, evaluating and scaling learning agents in multi-agent environments. AI Commun. 35(4): 271-284 (2022) - [c9]Ian Gemp, Kevin R. McKee, Richard Everett, Edgar A. Duéñez-Guzmán, Yoram Bachrach, David Balduzzi, Andrea Tacchetti:
D3C: Reducing the Price of Anarchy in Multi-Agent Learning. AAMAS 2022: 498-506 - [c8]Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár:
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. AAMAS 2022: 507-515 - [i13]Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas, Alexander Sasha Vezhnevets, John P. Agapiou, Kevin R. McKee, Richard Everett, Janusz Marecki, Joel Z. Leibo, Thore Graepel:
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria. CoRR abs/2201.01816 (2022) - [i12]Avishkar Bhoopchand, Bethanie Brownfield, Adrian Collister, Agustin Dal Lago
Learning Robust Real-Time Cultural Transmission without Human Data. CoRR abs/2203.00715 (2022) - [i11]Elise van der Pol, Ian Gemp, Yoram Bachrach, Richard Everett:
Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering. CoRR abs/2207.14589 (2022) - [i10]Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments. CoRR abs/2209.10958 (2022) - 2021
- [c7]Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes:
Modelling Cooperation in Network Games with Spatio-Temporal Complexity. AAMAS 2021: 1455-1457 - [c6]DJ Strouse, Kevin R. McKee, Matt M. Botvinick, Edward Hughes, Richard Everett:
Collaborating with Humans without Human Data. NeurIPS 2021: 14502-14515 - [i9]Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes:
Modelling Cooperation in Network Games with Spatio-Temporal Complexity. CoRR abs/2102.06911 (2021) - [i8]Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, Richard Everett:
Quantifying environment and population diversity in multi-agent reinforcement learning. CoRR abs/2102.08370 (2021) - [i7]Ian Gemp, Rahul Savani
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. CoRR abs/2106.01285 (2021) - [i6]DJ Strouse, Kevin R. McKee, Matt M. Botvinick, Edward Hughes, Richard Everett:
Collaborating with Humans without Human Data. CoRR abs/2110.08176 (2021) - 2020
- [j2]Karl Tuyls
Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. 34(1): 7 (2020) - [j1]Yoram Bachrach
Negotiating team formation using deep reinforcement learning. Artif. Intell. 288: 103356 (2020) - [c5]Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach:
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. NeurIPS 2020 - [i5]Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach:
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. CoRR abs/2006.04635 (2020) - [i4]Ian Gemp, Kevin R. McKee, Richard Everett, Edgar A. Duéñez-Guzmán, Yoram Bachrach, David Balduzzi, Andrea Tacchetti:
D3C: Reducing the Price of Anarchy in Multi-Agent Learning. CoRR abs/2010.00575 (2020) - [i3]Raphael Köster, Kevin R. McKee, Richard Everett, Laura Weidinger, William S. Isaac, Edward Hughes, Edgar A. Duéñez-Guzmán, Thore Graepel, Matthew M. Botvinick, Joel Z. Leibo:
Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences. CoRR abs/2010.09054 (2020) - [i2]Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel:
Negotiating Team Formation Using Deep Reinforcement Learning. CoRR abs/2010.10380 (2020)
2010 – 2019
- 2019
- [c4]Richard Everett, Adam D. Cobb, Andrew Markham, Stephen J. Roberts:
Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents. AAMAS 2019: 1943-1945 - 2018
- [c3]Richard Everett, Stephen J. Roberts:
Learning Against Non-Stationary Agents with Opponent Modelling and Deep Reinforcement Learning. AAAI Spring Symposia 2018 - [c2]Adam D. Cobb, Richard Everett, Andrew Markham
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus. KDD 2018: 1254-1262 - [i1]Adam D. Cobb, Richard Everett, Andrew Markham, Stephen J. Roberts:
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus. CoRR abs/1802.10446 (2018) - 2016
- [c1]Richard M. Everett, Jason R. C. Nurse, Arnau Erola:
The anatomy of online deception: what makes automated text convincing? SAC 2016: 1115-1120
Coauthor Index
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