Richard Everett

26 papers A* 3A 4Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas. CoRR Udari Madhushani, Kevin R. McKee, John P. Agapiou, Joel Z. Leibo, Richard Everett, Thomas W. Anthony, Edward Hughes, Karl Tuyls, Edgar A. Duéñez-Guzmán
2022	A	`conf`	D3C: Reducing the Price of Anarchy in Multi-Agent Learning. AAMAS Ian Gemp, Kevin R. McKee, Richard Everett, Edgar A. Duéñez-Guzmán, Yoram Bachrach, David Balduzzi, Andrea Tacchetti
2022	J	`jnl`	Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments. CoRR 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, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls
2022	J	`jnl`	Developing, evaluating and scaling learning agents in multi-agent environments. AI Commun. 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, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls
2022	J	`jnl`	Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria. CoRR 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
2022	J	`jnl`	Learning Robust Real-Time Cultural Transmission without Human Data. CoRR Avishkar Bhoopchand, Bethanie Brownfield, Adrian Collister, Agustin Dal Lago, Ashley Edwards, Richard Everett, Alexandre Fréchette, Yanko Gitahy Oliveira, Edward Hughes, Kory W. Mathewson, Piermaria Mendolicchio, Julia Pawar, Miruna Pislar, Alex Platonov, Evan Senter, Sukhdeep Singh, Alexander Zacherl, Lei M. Zhang
2022	J	`jnl`	Quantifying the effects of environment and population diversity in multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, Richard Everett
2022	A	`conf`	Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. AAMAS Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
2022	J	`jnl`	Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering. CoRR Elise van der Pol, Ian Gemp, Yoram Bachrach, Richard Everett
2021	A*	`conf`	Collaborating with Humans without Human Data. NeurIPS DJ Strouse, Kevin R. McKee, Matt M. Botvinick, Edward Hughes, Richard Everett
2021	J	`jnl`	Collaborating with Humans without Human Data. CoRR DJ Strouse, Kevin R. McKee, Matt M. Botvinick, Edward Hughes, Richard Everett
2021	A	`conf`	Modelling Cooperation in Network Games with Spatio-Temporal Complexity. AAMAS Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes
2021	J	`jnl`	Modelling Cooperation in Network Games with Spatio-Temporal Complexity. CoRR Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes
2021	J	`jnl`	Quantifying environment and population diversity in multi-agent reinforcement learning. CoRR Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, Richard Everett
2021	J	`jnl`	Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. CoRR Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
2020	J	`jnl`	Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. Karl Tuyls, Julien Pérolat, Marc Lanctot, Edward Hughes, Richard Everett, Joel Z. Leibo, Csaba Szepesvári, Thore Graepel
2020	J	`jnl`	D3C: Reducing the Price of Anarchy in Multi-Agent Learning. CoRR Ian Gemp, Kevin R. McKee, Richard Everett, Edgar A. Duéñez-Guzmán, Yoram Bachrach, David Balduzzi, Andrea Tacchetti
2020	A*	`conf`	Learning to Play No-Press Diplomacy with Best Response Policy Iteration. NeurIPS 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
2020	J	`jnl`	Learning to Play No-Press Diplomacy with Best Response Policy Iteration. CoRR 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
2020	J	`jnl`	Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences. CoRR 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
2020	J	`jnl`	Negotiating Team Formation Using Deep Reinforcement Learning. CoRR Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
2020	J	`jnl`	Negotiating team formation using deep reinforcement learning. Artif. Intell. Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
2019	A	`conf`	Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents. AAMAS Richard Everett, Adam D. Cobb, Andrew Markham, Stephen J. Roberts
2018	A*	`conf`	Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus. KDD Adam D. Cobb, Richard Everett, Andrew Markham, Stephen J. Roberts
2018	J	`jnl`	Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus. CoRR Adam D. Cobb, Richard Everett, Andrew Markham, Stephen J. Roberts
2018	—	`conf`	Learning Against Non-Stationary Agents with Opponent Modelling and Deep Reinforcement Learning. AAAI Spring Symposia Richard Everett, Stephen J. Roberts