Edward Hughes
Edward Hughes
Staff Research Engineer, DeepMind
Email verificata su - Home page
Citata da
Citata da
Social influence as intrinsic motivation for multi-agent deep reinforcement learning
N Jaques, A Lazaridou, E Hughes, C Gulcehre, P Ortega, DJ Strouse, ...
International conference on machine learning, 3040-3049, 2019
The hanabi challenge: A new frontier for ai research
N Bard, JN Foerster, S Chandar, N Burch, M Lanctot, HF Song, E Parisotto, ...
Artificial Intelligence 280, 103216, 2020
Inequity aversion improves cooperation in intertemporal social dilemmas
E Hughes, JZ Leibo, M Phillips, K Tuyls, E Dueez-Guzman, ...
Advances in neural information processing systems 31, 2018
OpenSpiel: A framework for reinforcement learning in games
M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Prolat, ...
arXiv preprint arXiv:1908.09453, 2019
Learning to follow language instructions with adversarial reward induction
D Bahdanau, F Hill, J Leike, E Hughes, P Kohli, E Grefenstette
arXiv preprint arXiv:1806.01946, 6-9, 2018
Bayesian action decoder for deep multi-agent reinforcement learning
J Foerster, F Song, E Hughes, N Burch, I Dunning, S Whiteson, ...
International Conference on Machine Learning, 1942-1951, 2019
Open problems in cooperative AI
A Dafoe, E Hughes, Y Bachrach, T Collins, KR McKee, JZ Leibo, K Larson, ...
arXiv preprint arXiv:2012.08630, 2020
Causal reasoning from meta-reinforcement learning
I Dasgupta, J Wang, S Chiappa, J Mitrovic, P Ortega, D Raposo, ...
arXiv preprint arXiv:1901.08162, 2019
Autocurricula and the emergence of innovation from social interaction: A manifesto for multi-agent intelligence research
JZ Leibo, E Hughes, M Lanctot, T Graepel
arXiv preprint arXiv:1903.00742, 2019
Evolving intrinsic motivations for altruistic behavior
JX Wang, E Hughes, C Fernando, WM Czarnecki, EA Duez-Guzmn, ...
arXiv preprint arXiv:1811.05931, 2018
A generalized training approach for multiagent learning
P Muller, S Omidshafiei, M Rowland, K Tuyls, J Perolat, S Liu, D Hennes, ...
arXiv preprint arXiv:1909.12823, 2019
Collaborating with humans without human data
DJ Strouse, K McKee, M Botvinick, E Hughes, R Everett
Advances in Neural Information Processing Systems 34, 14502-14515, 2021
Social diversity and social preferences in mixed-motive reinforcement learning
KR McKee, I Gemp, B McWilliams, EA Duez-Guzmn, E Hughes, ...
arXiv preprint arXiv:2002.02325, 2020
Learning reciprocity in complex sequential social dilemmas
T Eccles, E Hughes, J Kramr, S Wheelwright, JZ Leibo
AAMAS, 1934-1936, 2019
Learning to incentivize other learning agents
J Yang, A Li, M Farajtabar, P Sunehag, E Hughes, H Zha
Advances in Neural Information Processing Systems 33, 15208-15219, 2020
Malthusian reinforcement learning
JZ Leibo, J Perolat, E Hughes, S Wheelwright, AH Marblestone, ...
arXiv preprint arXiv:1812.07019, 2018
The connected prescription for form factors in twistor space
A Brandhuber, E Hughes, R Panerai, B Spence, G Travaglini
Journal of High Energy Physics 2016 (11), 1-17, 2016
Bounds and dynamics for empirical game theoretic analysis
K Tuyls, J Perolat, M Lanctot, E Hughes, R Everett, JZ Leibo, ...
Autonomous Agents and Multi-Agent Systems 34, 1-30, 2020
Reinforcement learning agents acquire flocking and symbiotic behaviour in simulated ecosystems
P Sunehag, G Lever, S Liu, J Merel, N Heess, JZ Leibo, E Hughes, ...
ALIFE 2019: The 2019 Conference on Artificial Life, 103-110, 2019
Negotiating team formation using deep reinforcement learning
Y Bachrach, R Everett, E Hughes, A Lazaridou, JZ Leibo, M Lanctot, ...
Artificial Intelligence 288, 103356, 2020
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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