Fetching the paper…
Reading the bibliography…
We study the problem of emergent communication, in which language arises because speakers and listeners must communicate information in order to solve tasks.
Stochastic games
L. S. Shapley · 1953
Earlier work this paper cites.
Utterer’s meaning, sentence-meaning, and word-meaning
H Paul Grice · 1968
Earlier work this paper cites.
Paul grice and the philosophy of language
Stephen Neale · 1992
Earlier work this paper cites.
Multi-agent reinforcement learning: Independent versus cooperative agents
Ming Tan · 1993
Earlier work this paper cites.
Markov games as a framework for multi-agent reinforcement learning
Michael L. Littman · 1994
Earlier work this paper cites.
Robocup: The robot world cup initiative
Hiroaki Kitano, Minoru Asada, Yasuo Kuniyoshi, Itsuki Noda, and Eiichi Osawa · 1997
Earlier work this paper cites.
The dynamics of reinforcement learning in cooperative multiagent systems
Caroline Claus and Craig Boutilier · 1998
Earlier work this paper cites.
The complexity of decentralized control of Markov Decision Processes
Daniel S. Bernstein, Shlomo Zilberstein, and Neil Immerman · 2000
Earlier work this paper cites.
An algorithm for distributed reinforcement learning in cooperative multi-agent systems
Martin Lauer and Martin A. Riedmiller · 2000
Earlier work this paper cites.
Evolving grounded communication for robots
Luc Steels · 2003
Earlier work this paper cites.
Progress in the simulation of emergent communication and language
Kyle Wagner, James A Reggia, Juan Uriagereka, and Gerald S Wilkinson · 2003
Earlier work this paper cites.
Dynamic programming for partially observable stochastic games
Eric A. Hansen, Daniel S. Bernstein, and Shlomo Zilberstein · 2004
Earlier work this paper cites.
The world of Independent learners is not Markovian
Guillaume J. Laurent, Laëtitia Matignon, and Nadine Le Fort-Piat · 2011
Earlier work this paper cites.
Lecture 6a: Overview of mini–batch gradient descent
G. Hinton, N. Srivastava, , and K. Swersky · 2012
Cited alongside, same era.
Coordinated multi-robot exploration under communication constraints using decentralized markov decision processes
Laëtitia Matignon, Laurent Jeanpierre, and Abdel-Illah Mouaddib · 2012
Cited alongside, same era.
Independent reinforcement learners in cooperative markov games: a survey regarding coordination problems
Laëtitia Matignon, Guillaume J. Laurent, and Nadine Le Fort-Piat · 2012
Cited alongside, same era.
An overview of recent progress in the study of distributed multi-agent coordination
Yongcan Cao, Wenwu Yu, Wei Ren, and Guanrong Chen · 2013
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Open sourcing Sonnet - a new library for constructing neural networks
Malcolm Reynolds, Gabriel Barth-Maron, Frederic Besse, Diego de Las Casas, Andreas Fidjeland, Tim Green, Andria Puigdomenech, Sébastien Racanière, Jack Rae, and Fabio Viola · 2017
Later among the works it cites.
Emergent complexity via multi-agent competition
Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, and Igor Mordatch · 2018
Later among the works it cites.
Emergent communication through negotiation
Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z Leibo, Karl Tuyls, and Stephen Clark · 2018
Later among the works it cites.
Tarmac: Targeted multi-agent communication
Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael Rabbat, and Joelle Pineau · 2018
Later among the works it cites.
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
L. Espeholt, H. Soyer, R. Munos, K. Simonyan, V. Mnih, T. Ward, Y. Doron, V. Firoiu, T. Harley, I. Dunning, S. Legg, and K. Kavukcuoglu · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Learning to communicate with deep multi-agent reinforcement learning
Jakob Foerster, Ioannis Alexandros Assael, Nando de Freitas, and Shimon Whiteson · 2016
Cited alongside, same era.
Cooperation and communication in multiagent deep reinforcement learning
Matthew John Hausknecht · 2016
Cited alongside, same era.
Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Learning multiagent communication with backpropagation
Sainbayar Sukhbaatar, Arthur Szlam, and Rob Fergus · 2016
Cited alongside, same era.
Natural language does not emerge’naturally’in multi-agent dialog
Satwik Kottur, José MF Moura, Stefan Lee, and Dhruv Batra · 2017
Cited alongside, same era.
Multi-agent reinforcement learning in sequential social dilemmas
Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, and Thore Graepel · 2017
Cited alongside, same era.
Multi-agent actor-critic for mixed cooperative-competitive environments
Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, OpenAI Pieter Abbeel, and Igor Mordatch · 2017
Cited alongside, same era.
Later among the works it cites.
Counterfactual multi-agent policy gradients
Jakob N. Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson · 2018
Later among the works it cites.
Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, and Thore Graepel · 2018
Later among the works it cites.
Emergence of linguistic communication from referential games with symbolic and pixel input
Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls, and Stephen Clark · 2018
Later among the works it cites.
Emergence of grounded compositional language in multi-agent populations
Igor Mordatch and Pieter Abbeel · 2018
Later among the works it cites.
Intrinsic social motivation via causal influence in multi-agent rl
Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Caglar Gulcehre, Pedro A Ortega, DJ Strouse, Joel Z Leibo, and Nando de Freitas · 2019
Closest in time.
Joel Z. Leibo, Edward Hughes, Marc Lanctot, and Thore Graepel · 2019
Closest in time.
On the pitfalls of measuring emergent communication
Ryan Lowe, Jakob Foerster, Y-Lan Boureau, Joelle Pineau, and Yann Dauphin · 2019
Closest in time.