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Recent research on reinforcement learning in pure-conflict and pure-common interest games has emphasized the importance of population heterogeneity.
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Retrospectives: The origins of the representative agent
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Multiagent reinforcement learning in the iterated prisoner’s dilemma
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Population viscosity and the evolution of altruism
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What is the difference between controlling for mean versus median income in analyses of income inequality?
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Intrinsically motivated reinforcement learning
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Group competition, reproductive leveling, and the evolution of human altruism
Samuel Bowles · 2006
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Cooperation, punishment, and the evolution of human institutions
Joseph Henrich · 2006
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Social heterosis and the maintenance of genetic diversity
P. Nonacs and K. M. Kapheim · 2007
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Constraining free riding in public goods games: Designated solitary punishers can sustain human cooperation
Rick O’Gorman, Joseph Henrich, and Mark Van Vugt · 2008
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Social Value Orientation and cooperation in social dilemmas: A meta-analysis
Daniel Balliet, Craig Parks, and Jeff Joireman · 2009
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Social value orientation moderates ingroup love but not outgroup hate in competitive intergroup conflict
Consequentialist conditional cooperation in social dilemmas with imperfect information
Alexander Peysakhovich and Adam Lerer · 2017
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Impala: Scalable distributed deep-RL with importance weighted actor-learner architectures
Lasse Espeholt, Hubert Soyer, Remi Munos, Karen Simonyan, Volodymir Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, et al · 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 R. McKee, Raphael Koster, et al · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Carsten K. W. de Dreu · 2010
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Social categorization and the self-concept: A social cognitive theory of group behavior
John C. Turner · 2010
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A history of prosocial research
C. Daniel Batson · 2012
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Decentralized control of partially observable Markov decision processes
Christopher Amato, Girish Chowdhary, Alborz Geramifard, N. Kemal Üre, and Mykel J. Kochenderfer · 2013
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Power to the people: The role of humans in interactive machine learning
Saleema Amershi, Maya Cakmak, William Bradley Knox, and Todd Kulesza · 2014
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Social Value Orientation: Theoretical and measurement issues in the study of social preferences
Ryan O. Murphy and Kurt A. Ackermann · 2014
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Other-regarding preferences: A selective survey of experimental results
David J. Cooper and John H. Kagel · 2016
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Alexander Peysakhovich and Adam Lerer · 2018
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A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, et al · 2018
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Value-decomposition networks for cooperative multi-agent learning based on team reward
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinicius Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, et al · 2018
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Guidelines for human-AI interaction
Saleema Amershi, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N Bennett, Kori Inkpen, et al · 2019
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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, et al · 2019
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On the utility of learning about humans for human-AI coordination
Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, and Anca Dragan · 2019
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Blueprint: The Evolutionary Origins of a Good Society
Nicholas Christakis · 2019
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The Imitation Game: Learned reciprocity in markov games
Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, and Joel Z. Leibo · 2019
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Drawing on different disciplines: Macroeconomic agent-based models
Andrew G. Haldane and Arthur E. Turrell · 2019
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Behavioural evidence for a transparency–efficiency tradeoff in human–machine cooperation
Fatimah Ishowo-Oloko, Jean-François Bonnefon, Zakariyah Soroye, Jacob Crandall, Iyad Rahwan, and Talal Rahwan · 2019
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Human-level performance in 3d multiplayer games with population-based reinforcement learning
Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio Garcia Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, et al · 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, D. J. Strouse, Joel Z. Leibo, and Nando De Freitas · 2019
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Grandmaster level in StarCraft II using multi-agent reinforcement learning
Oriol Vinyals, Igor Babuschkin, Wojciech M Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, et al · 2019
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Evolving intrinsic motivations for altruistic behavior
Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, and Joel Z. Leibo · 2019
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