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In this work, we integrate `social' interactions into the MARL setup through a user-defined relational network and examine the effects of agent-agent relations on the rise of emergent behaviors.
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Yoshinobu Bochi, Tadachika Ozono, and Toramatsu Shintani · 2003
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Frans De Waal · 2010
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Don Edward Beck and Christopher C Cowan · 2014
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It’s all about relationships: how human relational development and social structures dictate product design in the socio-sphere
Charles Pezeshki and Ryan Kelley · 2014
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Formalization of weak emergence in multiagent systems
Claudia Szabo and Yong Meng Teo · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Learning to communicate with deep multi-agent reinforcement learning
Jakob Foerster, Ioannis Alexandros Assael, Nando De Freitas, and Shimon Whiteson · 2016
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Multi-agent actor-critic for mixed cooperative-competitive environments
Joel Z Leibo, Edward Hughes, Marc Lanctot, and Thore Graepel · 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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Emergent tool use from multi-agent autocurricula. arxiv
Bowen Baker, Ingmar Kanitscheider, Todor Markov, Yi Wu, Glenn Powell, Bob McGrew, and Igor Mordatch · 2019
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A review of cooperative multi-agent deep reinforcement learning
Afshin OroojlooyJadid and Davood Hajinezhad · 2019
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Decentralized multi-agent reinforcement learning with networked agents: Recent advances
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Ryan Lowe, Yi I Wu, Aviv Tamar, Jean Harb, OpenAI Pieter Abbeel, and Igor Mordatch · 2017
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Deep decentralized multi-task multi-agent reinforcement learning under partial observability
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P How, and John Vian · 2017
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Multi-agent reinforcement learning in sequential social dilemmas
Joel Z Leibo, Vinicius Zambaldi, Marc Lanctot, Janusz Marecki, and Thore Graepel · 2017
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Stabilising experience replay for deep multi-agent reinforcement learning
Jakob Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip HS Torr, Pushmeet Kohli, and Shimon Whiteson · 2017
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Order out of chaos: Man’s new dialogue with nature
Ilya Prigogine and Isabelle Stengers · 2018
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Prosocial learning agents solve generalized stag hunts better than selfish ones
Alexander Peysakhovich and Adam Lerer · 2018
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Kaiqing Zhang, Zhuoran Yang, and Tamer Başar · 2019
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Dealing with non-stationarity in multi-agent deep reinforcement learning
Georgios Papoudakis, Filippos Christianos, Arrasy Rahman, and Stefano V Albrecht · 2019
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Thermodynamics-inspired macroscopic states of bounded swarms
Hossein Haeri, Kshitij Jerath, and Jacob Leachman · 2020
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Social diversity and social preferences in mixed-motive reinforcement learning
Kevin R McKee, Ian Gemp, Brian McWilliams, Edgar A Duéñez-Guzmán, Edward Hughes, and Joel Z Leibo · 2020
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Learning to cooperate: Emergent communication in multi-agent navigation
Ivana Kajić, Eser Aygün, and Doina Precup · 2020
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Emergent multi-agent communication in the deep learning era
Angeliki Lazaridou and Marco Baroni · 2020
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Multi-objective multi-agent decision making: a utility-based analysis and survey
Roxana Rădulescu, Patrick Mannion, Diederik M Roijers, and Ann Nowé · 2020
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