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Multi-agent reinforcement learning (MARL) models multiple agents that interact and learn within a shared environment.
Optimal inventory policy
Kenneth J Arrow, Theodore Harris, and Jacob Marschak · 1951
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Inventory theory and consumer behavior
Alan S Blinder · 1990
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Inventory management: principles, concepts and techniques
John W Toomey · 2000
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Traffic simulation with sumo–simulation of urban mobility
Daniel Krajzewicz · 2010
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Multi-agent reinforcement learning: An overview
Lucian Buşoniu, Robert Babuška, and Bart De Schutter · 2010
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Experience replay for real-time reinforcement learning control
Sander Adam, Lucian Busoniu, and Robert Babuska · 2011
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Quantitative models for supply chain management
Sridhar Tayur, Ram Ganeshan, and Michael Magazine · 2012
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A decision-making method for autonomous vehicles based on simulation and reinforcement learning
Rui Zheng, Chunming Liu, and Qi Guo · 2013
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Supply chain management: An overview
Hartmut Stadtler · 2014
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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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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
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Starcraft II: A new challenge for reinforcement learning
Oriol Vinyals, Timo Ewalds, Sergey Bartunov, Petko Georgiev, Alexander Sasha Vezhnevets, Michelle Yeo, Alireza Makhzani, Heinrich Küttler, John Agapiou, Julian Schrittwieser, et al · 2017
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Deep reinforcement learning approaches for process control
SPK Spielberg, RB Gopaluni, and PD Loewen · 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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Robust adversarial reinforcement learning
Lerrel Pinto, James Davidson, Rahul Sukthankar, and Abhinav Gupta · 2017
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Reinforcement Learning: An Introduction
Richard S Sutton and Andrew G Barto · 2018
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Starcraft micromanagement with reinforcement learning and curriculum transfer learning
Kun Shao, Yuanheng Zhu, and Dongbin Zhao · 2018
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David Rohde, Stephen Bonner, Travis Dunlop, Flavian Vasile, and Alexandros Karatzoglou · 2018
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Mean field multi-agent reinforcement learning
Yaodong Yang, Rui Luo, Minne Li, Ming Zhou, Weinan Zhang, and Jun Wang · 2018
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Discovering and removing exogenous state variables and rewards for reinforcement learning
Thomas Dietterich, George Trimponias, and Zhitang Chen · 2018
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Emergence of grounded compositional language in multi-agent populations
Igor Mordatch and Pieter Abbeel · 2018
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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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Multi-agent reinforcement learning for networked system control
Tianshu Chu, Sandeep Chinchali, and Sachin Katti · 2020
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Google research football: A novel reinforcement learning environment
Karol Kurach, Anton Raichuk, Piotr Stańczyk, Michał Zając, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, et al · 2020
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Or-gym: A reinforcement learning library for operations research problems
Christian D Hubbs, Hector D Perez, Owais Sarwar, Nikolaos V Sahinidis, Ignacio E Grossmann, and John M Wassick · 2020
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Monotonic value function factorisation for deep multi-agent reinforcement learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder De Witt, Gregory Farquhar, Jakob Foerster, and Shimon Whiteson · 2020
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A deep reinforcement learning approach for inventory management in retail
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Dota 2 with large scale deep reinforcement learning
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Applications of reinforcement learning in energy systems
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Multiadvisor reinforcement learning for multiagent multiobjective smart home energy control
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Deep reinforcement learning for autonomous driving: A survey
B Ravi Kiran, Ibrahim Sobh, Victor Talpaert, Patrick Mannion, Ahmad A Al Sallab, Senthil Yogamani, and Patrick Pérez · 2021
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Reinforcement learning in economics and finance
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Facmac: Factored multi-agent centralised policy gradients
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Maniskill: Generalizable manipulation skill benchmark with large-scale demonstrations
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Simulation of inventory management systems in retail stores: A case study
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A deep q-learning-based optimization of the inventory control in a linear process chain
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Collective intelligence for deep learning: A survey of recent developments
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Multi-agent reinforcement learning with shared resources for inventory management
Yuandong Ding, Mingxiao Feng, Guozi Liu, Wei Jiang, Chuheng Zhang, Li Zhao, Lei Song, Houqiang Li, Yan Jin, and Jiang Bian · 2022
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Towards generalizable reinforcement learning for trade execution
Chuheng Zhang, Yitong Duan, Xiaoyu Chen, Jianyu Chen, Jian Li, and Li Zhao · 2023
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Gobigger: A scalable platform for cooperative-competitive multi-agent interactive simulation
Ming Zhang, Shenghan Zhang, Zhenjie Yang, Lekai Chen, Jinliang Zheng, Chao Yang, Chuming Li, Hang Zhou, Yazhe Niu, and Yu Liu · 2023
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