Edward Hughes

According to our database, Edward Hughes authored at least 43 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Open-Endedness is Essential for Artificial Superhuman Intelligence.

Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel

CoRR, 2024

Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning.

Jonathan Cook, Chris Lu, Edward Hughes, Joel Z. Leibo, Jakob N. Foerster

CoRR, 2024

The Ethics of Advanced AI Assistants.

Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks, Verena Rieser, Hasan Iqbal, Nenad Tomasev, Ira Ktena, Zachary Kenton, Mikel Rodriguez, Seliem El-Sayed, Sasha Brown, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema Marchal, Conor Griffin, Juan Mateos-Garcia, Laura Weidinger, Winnie Street, Benjamin Lange, Alex Ingerman, Alison Lentz, Reed Enger, Andrew Barakat, Victoria Krakovna, John Oliver Siy, Zeb Kurth-Nelson, Amanda McCroskery, Vijay Bolina, Harry Law, Murray Shanahan, Lize Alberts, Borja Balle, Sarah de Haas, Yetunde Ibitoye, Allan Dafoe, Beth Goldberg, Sébastien Krier, Alexander Reese, Sims Witherspoon, Will Hawkins, Maribeth Rauh, Don Wallace, Matija Franklin, Josh A. Goldstein, Joel Lehman, Michael Klenk, Shannon Vallor, Courtney Biles, Meredith Ringel Morris, Helen King, Blaise Agüera y Arcas, William Isaac, James Manyika

CoRR, 2024

Towards a Pretrained Model for Restless Bandits via Multi-arm Generalization.

Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Genie: Generative Interactive Environments.

Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: Open-Endedness is Essential for Artificial Superhuman Intelligence.

Edward Hughes, Michael D. Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Zero Shot Learning in Restless Multi-armed Bandits.

Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

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

Udari Madhushani, Kevin R. McKee, John P. Agapiou, Joel Z. Leibo, Richard Everett, Thomas W. Anthony, Edward Hughes, Karl Tuyls, Edgar A. Duéñez-Guzmán

CoRR, 2023

Human-Timescale Adaptation in an Open-Ended Task Space.

Adaptive Agent Team, Jakob Bauer, Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei Zhang

CoRR, 2023

Human-Timescale Adaptation in an Open-Ended Task Space.

Jakob Bauer, Kate Baumli, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Satinder Singh, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei M. Zhang

Proceedings of the International Conference on Machine Learning, 2023

2022

Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning.

Michael Bradley Johanson, Edward Hughes, Finbarr Timbers, Joel Z. Leibo

CoRR, 2022

Learning Robust Real-Time Cultural Transmission without Human Data.

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

CoRR, 2022

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

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

AI Commun., 2022

2021

Deep reinforcement learning models the emergent dynamics of human cooperation.

Kevin R. McKee, Edward Hughes, Tina O. Zhu, Martin J. Chadwick, Raphael Koster, Antonio García Castañeda, Charlie Beattie, Thore Graepel, Matthew M. Botvinick, Joel Z. Leibo

CoRR, 2021

Neural Recursive Belief States in Multi-Agent Reinforcement Learning.

Pol Moreno, Edward Hughes, Kevin R. McKee, Bernardo Ávila Pires, Théophane Weber

CoRR, 2021

Collaborating with Humans without Human Data.

DJ Strouse, Kevin R. McKee, Matt M. Botvinick, Edward Hughes, Richard Everett

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.

Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Open Problems in Cooperative AI.

Allan Dafoe, Edward Hughes, Yoram Bachrach, Tantum Collins, Kevin R. McKee, Joel Z. Leibo, Kate Larson, Thore Graepel

CoRR, 2020

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

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

CoRR, 2020

The Hanabi challenge: A new frontier for AI research.

Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling

Artif. Intell., 2020

Negotiating team formation using deep reinforcement learning.

Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel

Artif. Intell., 2020

Bounds and dynamics for empirical game theoretic analysis.

Karl Tuyls, Julien Pérolat, Marc Lanctot, Edward Hughes, Richard Everett, Joel Z. Leibo, Csaba Szepesvári, Thore Graepel

Auton. Agents Multi Agent Syst., 2020

Learning to Incentivize Other Learning Agents.

Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes, Hongyuan Zha

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Generalized Training Approach for Multiagent Learning.

Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos

Proceedings of the 8th International Conference on Learning Representations, 2020

Smooth markets: A basic mechanism for organizing gradient-based learners.

David Balduzzi, Wojciech M. Czarnecki, Tom Anthony, Ian Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel

Proceedings of the 8th International Conference on Learning Representations, 2020

Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning.

Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games.

Edward Hughes, Thomas W. Anthony, Tom Eccles, Joel Z. Leibo, David Balduzzi, Yoram Bachrach

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

OpenSpiel: A Framework for Reinforcement Learning in Games.

Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas W. Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis

CoRR, 2019

Learning Reciprocity in Complex Sequential Social Dilemmas.

Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo

CoRR, 2019

Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research.

Joel Z. Leibo, Edward Hughes, Marc Lanctot, Thore Graepel

CoRR, 2019

Causal Reasoning from Meta-reinforcement Learning.

Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew M. Botvinick, Zeb Kurth-Nelson

CoRR, 2019

Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems.

Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel

Proceedings of the 2019 Conference on Artificial Life, 2019

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning.

Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas

Proceedings of the 36th International Conference on Machine Learning, 2019

Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning.

Jakob N. Foerster, H. Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew M. Botvinick, Michael Bowling

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning to Understand Goal Specifications by Modelling Reward.

Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Seyed Arian Hosseini, Pushmeet Kohli, Edward Grefenstette

Proceedings of the 7th International Conference on Learning Representations, 2019

Evolving Intrinsic Motivations for Altruistic Behavior.

Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Malthusian Reinforcement Learning.

Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

The Imitation Game: Learned Reciprocity in Markov games.

Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL.

Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas

CoRR, 2018

Learning to Follow Language Instructions with Adversarial Reward Induction.

Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Pushmeet Kohli, Edward Grefenstette

CoRR, 2018

Inequity aversion resolves intertemporal social dilemmas.

Edward Hughes, Joel Z. Leibo, Matthew G. Philips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel

CoRR, 2018

Inequity aversion improves cooperation in intertemporal social dilemmas.

Edward Hughes, Joel Z. Leibo, Matthew Phillips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Jointly Learning "What" and "How" from Instructions and Goal-States.

Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Pushmeet Kohli, Edward Grefenstette

Proceedings of the 6th International Conference on Learning Representations, 2018