Fetching the paper…
Reading the bibliography…
Multi-agent cooperation is an important feature of the natural world.
The Genetical Evolution of Social Behaviour. I
W.D. Hamilton. 1964a · 1964
Earlier work this paper cites.
The genetical evolution of social behaviour. II
William D Hamilton. 1964b · 1964
Earlier work this paper cites.
Group selection and kin selection
J Maynard Smith. 1964 · 1964
Earlier work this paper cites.
The evolution of reciprocal altruism
Robert L Trivers. 1971 · 1971
Earlier work this paper cites.
A theory of group selection
David Sloan Wilson. 1975 · 1975
Earlier work this paper cites.
The selfish gene Oxford university press
Richard Dawkins. 1976 · 1976
Earlier work this paper cites.
Rewards and punishments as selective incentives for collective action: theoretical investigations
Pamela Oliver. 1980 · 1980
Earlier work this paper cites.
The Evolution of Cooperation
Robert Axelrod and William D. Hamilton. 1981 · 1981
Earlier work this paper cites.
How learning can guide evolution
Geoffrey E Hinton and Steven J Nowlan. 1987 · 1987
Earlier work this paper cites.
Designing Neural Networks using Genetic Algorithms.. In ICGA
Geoffrey F Miller, Peter M Todd, and Shailesh U Hegde. 1989 · 1989
Earlier work this paper cites.
Do animals really recognize kin?
Alan Grafen et al · 1990
Earlier work this paper cites.
Covenants with and without a sword: Self-governance is possible
Elinor Ostrom, James Walker, and Roy Gardner. 1992 · 1992
Earlier work this paper cites.
Markov games as a framework for multi-agent reinforcement learning
Michael L Littman. 1994 · 1994
Earlier work this paper cites.
Learning to behave socially. In Third international conference on simulation of adaptive behavior
Maja J Mataric. 1994 · 1994
Earlier work this paper cites.
The major transitions in evolution
John Maynard Smith and Eors Szathmary. 1997 · 1997
Earlier work this paper cites.
Selfish genes: A green beard in the red fire ant
Laurent Keller and Kenneth G. Ross. 1998 · 1998
Earlier work this paper cites.
A Theory of Fairness, Competition, and Cooperation*
Ernst Fehr and Klaus M. Schmidt. 1999 · 1999
Earlier work this paper cites.
Cooperative coevolution: An architecture for evolving coadapted subcomponents
Mitchell A Potter and Kenneth A De Jong. 2000 · 2000
Earlier work this paper cites.
Cooperative coevolution of multi-agent systems
Chern Han Yong and Risto Miikkulainen. 2001 · 2001
Earlier work this paper cites.
Alleviating’overfitting’via genetically-regularised neural network
ZSH Chan, HW Ngan, AB Rad, and TK Ho. 2002 · 2002
Earlier work this paper cites.
Kin selection: Fact and fiction
Ashleigh Griffin and Stuart West. 2002 · 2002
Cited alongside, same era.
Evolving neural networks through augmenting topologies
Kenneth O Stanley and Risto Miikkulainen. 2002 · 2002
Cited alongside, same era.
All learning is local: Multi-agent learning in global reward games. In Advances in neural information processing systems
Yu-Han Chang, Tracey Ho, and Leslie P Kaelbling. 2004 · 2004
Cited alongside, same era.
Cooperation and competition in pathogenic bacteria
Ashleigh S Griffin, Stuart A West, and Angus Buckling. 2004 · 2004
Cited alongside, same era.
Cultural group selection, coevolutionary processes and large-scale cooperation
Joseph Henrich. 2004 · 2004
Cited alongside, same era.
Intrinsically Motivated Reinforcement Learning
Nuttapong Chentanez, Andrew G. Barto, and Satinder P. Singh. 2005 · 2005
Intrinsically motivated reinforcement learning: An evolutionary perspective
Satinder Singh, Richard L Lewis, Andrew G Barto, and Jonathan Sorg. 2010 · 2010
Later among the works it cites.
Horizontal gene transfer and the evolution of bacterial cooperation
Sorcha E McGinty, Daniel J Rankin, and Sam P Brown. 2011 · 2011
Later among the works it cites.
Power and corruption
Francisco Úbeda and Edgar A Duéñez-Guzmán. 2011 · 2011
Later among the works it cites.
Intrinsically Motivated Learning in Natural and Artificial Systems
Gianluca Baldassarre and Marco Mirolli. 2013 · 2013
Later among the works it cites.
Other-regarding preferences
David J Cooper and John H Kagel. 2016 · 2016
Later among the works it cites.
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, and Shimon Whiteson. 2016 · 2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Evolution of indirect reciprocity
Martin A Nowak and Karl Sigmund. 2005 · 2005
Cited alongside, same era.
Cooperative multi-agent learning: The state of the art
Liviu Panait and Sean Luke. 2005 · 2005
Cited alongside, same era.
The competitive advantage of sanctioning institutions
Özgür Gürerk, Bernd Irlenbusch, and Bettina Rockenbach. 2006 · 2006
Cited alongside, same era.
Nice guys finish first: The competitive altruism hypothesis
Charlie L Hardy and Mark Van Vugt. 2006 · 2006
Cited alongside, same era.
Altruism through beard chromodynamics
Vincent Jansen and Minus van Baalen. 2006 · 2006
Cited alongside, same era.
Five Rules for the Evolution of Cooperation
Martin A. Nowak. 2006 · 2006
Cited alongside, same era.
Later among the works it cites.
Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction. In CogSci
Max Kleiman-Weiner, Mark K. Ho, Joseph L. Austerweil, Michael L. Littman, and Joshua B. Tenenbaum. 2016 · 2016
Later among the works it cites.
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu. 2016 · 2016
Later among the works it cites.
Edoardo Conti, Vashisht Madhavan, Felipe Petroski Such, Joel Lehman, Kenneth O Stanley, and Jeff Clune. 2017 · 2017
Later among the works it cites.
Learning with Opponent-Learning Awareness
Jakob N. Foerster, Richard Y. Chen, Maruan Al-Shedivat, Shimon Whiteson, Pieter Abbeel, and Igor Mordatch. 2017 · 2017
Later among the works it cites.
Population based training of neural networks
Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, et al · 2017
Later among the works it cites.
Multi-agent reinforcement learning in sequential social dilemmas. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems
Joel Z Leibo, Vinicius Zambaldi, Marc Lanctot, Janusz Marecki, and Thore Graepel. 2017 · 2017
Later among the works it cites.
Maintaining cooperation in complex social dilemmas using deep reinforcement learning
Adam Lerer and Alexander Peysakhovich. 2017 · 2017
Later among the works it cites.
A multi-agent reinforcement learning model of common-pool resource appropriation
Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, and Thore Graepel. 2017 · 2017
Later among the works it cites.
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
Closest in time.
Meta Learning by the Baldwin Effect
Chrisantha Thomas Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, and Andrei A Rusu. 2018 · 2018
Closest in time.
Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, and Pieter Abbeel. 2018 · 2018
Closest in time.
Inequity aversion improves cooperation in intertemporal social dilemmas. In Advances in neural information processing systems (NIPS)
Edward Hughes, Joel Z Leibo, Matthew G Phillips, Karl Tuyls, Edgar A Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R McKee, Raphael Koster, et al · 2018
Closest in time.
Max Jaderberg, Wojciech M Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio Garcia Castaneda, Charles Beattie, Neil C Rabinowitz, Ari S Morcos, Avraham Ruderman, et al · 2018
Closest in time.
Consequentialist conditional cooperation in social dilemmas with imperfect information. In International Conference on Learning Representations
Alexander Peysakhovich and Adam Lerer. 2018 · 2018
Closest in time.