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As a fundamental problem for Artificial Intelligence, multi-agent system (MAS) is making rapid progress, mainly driven by multi-agent reinforcement learning (MARL) techniques.
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The vector field histogram-fast obstacle avoidance for mobile robots
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Ming Tan · 1993
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Markov games as a framework for multi-agent reinforcement learning
Michael L Littman · 1994
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Symbolic navigation with a generic map
Dongsung Kim and Ramakant Nevatia · 1999
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A probabilistic approach to collaborative multi-robot localization
Dieter Fox, Wolfram Burgard, Hannes Kruppa, and Sebastian Thrun · 2000
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Multiagent systems: A survey from a machine learning perspective
Peter Stone and Manuela Veloso · 2000
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Probabilistic robotics
Sebastian Thrun · 2002
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Multiple view geometry in computer vision
Richard Hartley and Andrew Zisserman · 2003
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Coordination and adaptation in impromptu teams
Michael Bowling and Peter McCracken · 2005
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Cooperative multi-agent learning: The state of the art
Liviu Panait and Sean Luke · 2005
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Artificial general intelligence
Ben Goertzel and Cassio Pennachin · 2007
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A comprehensive survey of multiagent reinforcement learning
Lucian Busoniu, Robert Babuska, and Bart De Schutter · 2008
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Democratic reason: Politics, collective intelligence, and the rule of the many
Helene Emilie Landemore · 2008
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Empirical evaluation of ad hoc teamwork in the pursuit domain
Samuel Barrett, Peter Stone, and Sarit Kraus · 2011
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Report on the second challenge on generating instructions in virtual environments (give-2.5)
Kristina Striegnitz, Alexandre Denis, Andrew Gargett, Konstantina Garoufi, Alexander Koller, and Mariët Theune · 2011
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Independent reinforcement learners in cooperative markov games: a survey regarding coordination problems
Laetitia Matignon, Guillaume J Laurent, and Nadine Le Fort-Piat · 2012
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Nonuniform deployment of autonomous agents in harbor-like environments
Suruz Miah, Bao Nguyen, François-Alex Bourque, and Davide Spinello · 2014
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Distributed coverage control for concave areas by a heterogeneous robot–swarm with visibility sensing constraints
Yiannis Kantaros, Michalis Thanou, and Anthony Tzes · 2015
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High-dimensional continuous control using generalized advantage estimation
John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel · 2015
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Distributed collaborative coverage-control schemes for non-convex domains
Yiannis Stergiopoulos, Michalis Thanou, and Anthony Tzes · 2015
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3d semantic parsing of large-scale indoor spaces
Iro Armeni, Ozan Sener, Amir R Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese · 2016
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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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Half field offense: An environment for multiagent learning and ad hoc teamwork
Matthew Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan, and Peter Stone · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Multirobot cooperative learning for semiautonomous control in urban search and rescue applications
Yugang Liu and Goldie Nejat · 2016
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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
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Learning multiagent communication with backpropagation
Sainbayar Sukhbaatar, Arthur Szlam, and Rob Fergus · 2016
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Emergent complexity via multi-agent competition
Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, and Igor Mordatch · 2017
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Home: A household multimodal environment
Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, and Aaron Courville · 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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Cooperative multi-agent control using deep reinforcement learning
Jayesh K Gupta, Maxim Egorov, and Mykel Kochenderfer · 2017
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Cognitive mapping and planning for visual navigation
Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, and Jitendra Malik · 2017
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A deep policy inference q-network for multi-agent systems
Zhang-Wei Hong, Shih-Yang Su, Tzu-Yun Shann, Yi-Hsiang Chang, and Chun-Yi Lee · 2017
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Ai2-thor: An interactive 3d environment for visual ai
Eric Kolve, Roozbeh Mottaghi, Winson Han, Eli VanderBilt, Luca Weihs, Alvaro Herrasti, Daniel Gordon, Yuke Zhu, Abhinav Gupta, and Ali Farhadi · 2017
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Multi-agent cooperation and the emergence of (natural) language
Angeliki Lazaridou, Alexander Peysakhovich, and Marco Baroni · 2017
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Touchdown: Natural language navigation and spatial reasoning in visual street environments
Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely, and Yoav Artzi · 2019
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Tarmac: Targeted multi-agent communication
Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Mike Rabbat, and Joelle Pineau · 2019
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A survey and critique of multiagent deep reinforcement learning
Pablo Hernandez-Leal, Bilal Kartal, and Matthew E Taylor · 2019
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Actor-attention-critic for multi-agent reinforcement learning
Shariq Iqbal and Fei Sha · 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 Castaneda, Charles Beattie, Neil C Rabinowitz, Ari S Morcos, Avraham Ruderman, et al · 2019
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Multi-agent actor-critic for mixed cooperative-competitive environments
Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, and Igor Mordatch · 2017
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Lenient multi-agent deep reinforcement learning
Gregory Palmer, Karl Tuyls, Daan Bloembergen, and Rahul Savani · 2017
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Peng Peng, Ying Wen, Yaodong Yang, Quan Yuan, Zhenkun Tang, Haitao Long, and Jun Wang · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Semantic scene completion from a single depth image
Shuran Song, Fisher Yu, Andy Zeng, Angel X Chang, Manolis Savva, and Thomas Funkhouser · 2017
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Neural slam: Learning to explore with external memory
Jingwei Zhang, Lei Tai, Joschka Boedecker, Wolfram Burgard, and Ming Liu · 2017
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Target-driven visual navigation in indoor scenes using deep reinforcement learning
Yuke Zhu, Roozbeh Mottaghi, Eric Kolve, Joseph J Lim, Abhinav Gupta, Li Fei-Fei, and Ali Farhadi · 2017
Cited alongside, same era.
Unnat Jain, Luca Weihs, Eric Kolve, Mohammad Rastegari, Svetlana Lazebnik, Ali Farhadi, Alexander G Schwing, and Aniruddha Kembhavi · 2019
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Learning to schedule communication in multi-agent reinforcement learning
Daewoo Kim, Sangwoo Moon, David Hostallero, Wan Ju Kang, Taeyoung Lee, Kyunghwan Son, and Yung Yi · 2019
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Pyrobot: An open-source robotics framework for research and benchmarking
Adithyavairavan Murali, Tao Chen, Kalyan Vasudev Alwala, Dhiraj Gandhi, Lerrel Pinto, Saurabh Gupta, and Abhinav Gupta · 2019
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Neural map: Structured memory for deep reinforcement learning
Emilio Parisotto and Ruslan Salakhutdinov · 2019
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The starcraft multi-agent challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder De Witt, Gregory Farquhar, Nantas Nardelli, Tim GJ Rudner, Chia-Man Hung, Philip HS Torr, Jakob Foerster, and Shimon Whiteson · 2019
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Habitat: A platform for embodied ai research
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, et al · 2019
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A multi-agent off-policy actor-critic algorithm for distributed reinforcement learning
Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Basar, and Ji Liu · 2019
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Multi-agent reinforcement learning: A selective overview of theories and algorithms
Kaiqing Zhang, Zhuoran Yang, and Tamer Başar · 2019
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Object goal navigation using goal-oriented semantic exploration
Devendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta, and Ruslan Salakhutdinov · 2020
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Learning to explore using active neural slam
Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta, Abhinav Gupta, and Ruslan Salakhutdinov · 2020
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Neural topological slam for visual navigation
Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, and Saurabh Gupta · 2020
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Soundspaces: Audio-visual navigation in 3d environments
Changan Chen, Unnat Jain, Carl Schissler, Sebastia Vicenc Amengual Gari, Ziad Al-Halah, Vamsi Krishna Ithapu, Philip Robinson, and Kristen Grauman · 2020
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Robothor: An open simulation-to-real embodied ai platform
Matt Deitke, Winson Han, Alvaro Herrasti, Aniruddha Kembhavi, Eric Kolve, Roozbeh Mottaghi, Jordi Salvador, Dustin Schwenk, Eli VanderBilt, Matthew Wallingford, et al · 2020
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Evolving graphical planner: Contextual global planning for vision-and-language navigation
Zhiwei Deng, Karthik Narasimhan, and Olga Russakovsky · 2020
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A cordial sync: Going beyond marginal policies for multi-agent embodied tasks
Unnat Jain, Luca Weihs, Eric Kolve, Ali Farhadi, Svetlana Lazebnik, Aniruddha Kembhavi, and Alexander Schwing · 2020
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Graph convolutional reinforcement learning
Jiechuan Jiang, Chen Dun, Tiejun Huang, and Zongqing Lu · 2020
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When2com: multi-agent perception via communication graph grouping
Yen-Cheng Liu, Junjiao Tian, Nathaniel Glaser, and Zsolt Kira · 2020
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Who2com: Collaborative perception via learnable handshake communication
Yen-Cheng Liu, Junjiao Tian, Chih-Yao Ma, Nathan Glaser, Chia-Wen Kuo, and Zsolt Kira · 2020
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Improving coordination in small-scale multi-agent deep reinforcement learning through memory-driven communication
Emanuele Pesce and Giovanni Montana · 2020
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Is independent learning all you need in the starcraft multi-agent challenge?
Christian Schroeder de Witt, Tarun Gupta, Denys Makoviichuk, Viktor Makoviychuk, Philip HS Torr, Mingfei Sun, and Shimon Whiteson · 2020
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igibson, a simulation environment for interactive tasks in large realisticscenes
Bokui Shen, Fei Xia, Chengshu Li, Roberto Martín-Martín, Linxi Fan, Guanzhi Wang, Shyamal Buch, Claudia D’Arpino, Sanjana Srivastava, Lyne P Tchapmi, et al · 2020
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Learning when to communicate at scale in multiagent cooperative and competitive tasks
Amanpreet Singh, Tushar Jain, and Sainbayar Sukhbaatar · 2020
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Active visual information gathering for vision-language navigation
Hanqing Wang, Wenguan Wang, Tianmin Shu, Wei Liang, and Jianbing Shen · 2020
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Interactive gibson benchmark: A benchmark for interactive navigation in cluttered environments
Fei Xia, William B Shen, Chengshu Li, Priya Kasimbeg, Micael Edmond Tchapmi, Alexander Toshev, Roberto Martín-Martín, and Silvio Savarese · 2020
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Multi-agent collaboration via reward attribution decomposition
Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E Gonzalez, and Yuandong Tian · 2020
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Structured scene memory for vision-language navigation
Hanqing Wang, Wenguan Wang, Wei Liang, Caiming Xiong, and Jianbing Shen · 2021
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The surprising effectiveness of mappo in cooperative, multi-agent games, 2021
Chao Yu, Akash Velu, Eugene Vinitsky, Yu Wang, Alexandre Bayen, and Yi Wu · 2021
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