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Social dilemmas are situations where groups of individuals can benefit from mutual cooperation but conflicting interests impede them from doing so.
Multi-agent reinforcement learning in sequential social dilemmas
Joel Leibo, Vinicius Zambaldi, Marc Lanctot, Janusz Marecki, and Thore Graepel · 2017
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A multi-agent reinforcement learning model of common-pool resource appropriation
Julien Perolat, Joel Z Leibo, Vinicius Zambaldi, Charles Beattie, Karl Tuyls, and Thore Graepel · 2017
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Group dynamics
Donelson R Forsyth · 2018
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Recurrent world models facilitate policy evolution
David Ha and Jürgen Schmidhuber · 2018
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Inequity aversion improves cooperation in intertemporal social dilemmas
Edward Hughes, Joel Z Leibo, Matthew Phillips, Karl Tuyls, Edgar Dueñez-Guzman, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin McKee, Raphael Koster, et al · 2018
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Learning latent dynamics for planning from pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, and James Davidson · 2019
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Social influence as intrinsic motivation for multi-agent deep reinforcement learning
Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Caglar Gulcehre, Pedro Ortega, DJ Strouse, Joel Z Leibo, and Nando De Freitas · 2019
Cited alongside, same era.
Social dilemmas
Samuel S Komorita · 2019
Cited alongside, same era.
Open problems in cooperative ai
Allan Dafoe, Edward Hughes, Yoram Bachrach, Tantum Collins, Kevin R McKee, Joel Z Leibo, Kate Larson, and Thore Graepel · 2020
Cited alongside, same era.
Mastering atari with discrete world models
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, and Jimmy Ba · 2020
Cited alongside, same era.
Scalable evaluation of multi-agent reinforcement learning with melting pot
Joel Z Leibo, Edgar A Dueñez-Guzman, Alexander Vezhnevets, John P Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, and Thore Graepel · 2021
Cited alongside, same era.
Information optimization and transferable state abstractions in deep reinforcement learning
Diego Gomez, Nicanor Quijano, and Luis Felipe Giraldo · 2022
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Emergent bartering behaviour in multi-agent reinforcement learning
Michael Bradley Johanson, Edward Hughes, Finbarr Timbers, and Joel Z Leibo · 2022
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A path towards autonomous machine intelligence
Yann LeCun · 2022
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On the principles of parsimony and self-consistency for the emergence of intelligence
Yi Ma, Doris Tsao, and Heung-Yeung Shum · 2022
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Reinforcement learning facilitates an optimal interaction intensity for cooperation
Zhao Song, Hao Guo, Danyang Jia, Matjaž Perc, Xuelong Li, and Zhen Wang · 2022
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Emergent social learning via multi-agent reinforcement learning
Kamal K Ndousse, Douglas Eck, Sergey Levine, and Natasha Jaques · 2021
Cited alongside, same era.
Stephan Zheng, Alexander Trott, Sunil Srinivasa, David C Parkes, and Richard Socher · 2022
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