A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems

Cited by (273)

Items 101–200 of 273

1. Procedural Content Generation: Better Benchmarks for Transfer Reinforcement Learning
   Muller-Brockhausen, Matthias, Preuss, Mike, Plaat, Aske · 2021 · 2021 IEEE Conference on Games (CoG)
2. Incremental Learning of Abnormalities in Autonomous Systems
   Hassan Zaal, Hafsa Iqbal, Damian Campo, Lucio Marcenaro, Carlo S. Regazzoni · 2019 · IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
3. Co-Evolving Multi-Agent Transfer Reinforcement Learning via Scenario Independent Representation
   Ayesha Siddiqua, Siming Liu, Ayesha Siddika Nipu, Anthony Harris, Yan Liu · 2024 · IEEE Access
4. A semi-centralized multi-agent RL framework for efficient irrigation scheduling
   Bernard Twum Agyeman, Benjamin Decardi‐Nelson, Jinfeng Liu, Sirish L. Shah · 2024 · Control Engineering Practice
5. A Q-values Sharing Framework for Multi-agent Reinforcement Learning under Budget Constraint
   Changxi Zhu, Ho-fung Leung, Shuyue Hu, Yi Cai · 2020 · ACM Transactions on Autonomous and Adaptive Systems
6. SATF: A Scalable Attentive Transfer Framework for Efficient Multiagent Reinforcement Learning
   Bin Chen, Zehong Cao, Quan Bai · 2024 · IEEE Transactions on Neural Networks and Learning Systems
7. A Fuzzy Curiosity-Driven Mechanism for Multi-Agent Reinforcement Learning
   Wenbai Chen, Haobin Shi, Jingchen Li, Kao‐Shing Hwang · 2021 · International Journal of Fuzzy Systems
8. Multi-agent reinforcement learning for safe lane changes by connected and autonomous vehicles: A survey
   Bharathkumar Hegde, Mélanie Bouroche · 2023 · AI Communications
9. Learning by Reusing Previous Advice in Teacher-Student Paradigm
   Changxi Zhu, Yi Cai, Ho-fung Leung, Shuyue Hu · 2020 · Adaptive Agents and Multi-Agents Systems
10. Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks
    Amin Rakhsha, Goran Radanović, Rati Devidze, Xiaojin Zhu, Adish Kumar Singla · 2020 · arXiv (Cornell University)
11. Intelligent Multiclass Skin Cancer Detection Using Convolution Neural Networks
    Reham Alabduljabbar, Hala Alshamlan · 2021 · Computers, materials & continua/Computers, materials & continua (Print)
12. Experience Sharing Based Memetic Transfer Learning for Multiagent Reinforcement Learning
    Tonghao Wang, Xingguang Peng, Yaochu Jin, Demin Xu · 2021 · Memetic Computing
13. Towards Deployment of Robust Cooperative AI Agents: An Algorithmic Framework for Learning Adaptive Policies
    Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, A. Singla · 2020 · Adaptive Agents and Multi-Agent Systems
14. Advances in Memetic Automaton: Toward Human-Like Autonomous Agents in Complex Multi-Agent Learning Problems
    Yaqing Hou, Xiangchao Yu, Yifeng Zeng, Ziqi Wei, Haijun Zhang, Hongwei Ge, Qiang Zhang · 2021 · IEEE Computational Intelligence Magazine
15. Multi-Agent Advisor Q-Learning
    Sriram Ganapathi Subramanian, Matthew Edmund Taylor, Kate S. Larson, Mark Crowley · 2022 · Journal of Artificial Intelligence Research
16. Collaborative training of heterogeneous reinforcement learning agents in environments with sparse rewards: what and when to share?
    Alain Andrés, Esther Villar-Rodríguez, Javier Del Ser · 2022 · Neural Computing and Applications
17. Knowledge transfer in multi-agent reinforcement learning with incremental number of agents
    Wenzhang Liu, Lu Dong, Jian Liu, Changyin Sun · 2022 · Journal of Systems Engineering and Electronics
18. Software Engineering for Collective Cyber-Physical Ecosystems
    Roberto Casadei, Gianluca Aguzzi, Giorgio Audrito, Ferruccio Damiani, Danilo Pianini, Giordano Scarso, Gianluca Torta, Mirko Viroli D · 2025 · ACM Transactions on Software Engineering and Methodology
19. Multi-agent reinforcement learning-based method for demand response of building HVAC systems
    Yiwen Zhang, Yang Zhao, Chaobo Zhang, Chenxin Feng · 2025 · Journal of Building Engineering
20. Transfer Reinforcement Learning for Combinatorial Optimization Problems
    Gleice Kelly Barbosa Souza, Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos de Oliveira, Daniela Carine Ramires de Oliveira, Erivelton G. Nepomuceno · 2024 · Algorithms
21. Accurate policy detection and efficient knowledge reuse against multi-strategic opponents
    Hao Chen, Quan Liu, Ke Fu, Jian Xin Huang, Chang Wang, Jianxing Gong · 2022 · Knowledge-Based Systems
22. Advising reinforcement learning toward scaling agents in continuous control environments with sparse rewards
    Hailin Ren, Pinhas Ben‐Tzvi · 2020 · Engineering Applications of Artificial Intelligence
23. Parallel Knowledge Transfer in Multi-Agent Reinforcement Learning
    Yongyuan Liang, Bangwei Li · 2020 · arXiv (Cornell University)
24. MACRPO: Multi-agent cooperative recurrent policy optimization
    Eshagh Kargar, Ville Kyrki · 2024 · Frontiers in Robotics and AI
25. Human attention guided multiagent hierarchical reinforcement learning for heterogeneous agents
    Dingbang Liu, Fenghui Ren, Jun Yan, Guoxin Su, Shohei Kato, Wen Gu, Minjie Zhang · 2025 · Knowledge-Based Systems
26. AdaptAUG: Adaptive Data Augmentation Framework for Multi-Agent Reinforcement Learning
    Xin Yu, Yongkai Tian, Li Wang, Pu Feng, Wenjun Wu, Rongye Shi · 2024 · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings
27. RapidLayout: Fast Hard Block Placement of FPGA-optimized Systolic Arrays Using Evolutionary Algorithm
    Niansong Zhang, Xiang Chen, Nachiket Kapre · 2022 · ACM Transactions on Reconfigurable Technology and Systems
28. Cooperative Multiagent Transfer Learning With Coalition Pattern Decomposition
    Tianze Zhou, Fubiao Zhang, Kun Shao, Zipeng Dai, Kai Li, Wenhan Huang, Weixun Wang, Bin Wang, Dong Li, Wulong Liu et al. · 2023 · IEEE Transactions on Games
29. Ask-AC: An Initiative Advisor-in-the-Loop Actor–Critic Framework
    Shunyu Liu, Kaixuan Chen, Na Yu, Jie Song, Zunlei Feng, Mingli Song · 2023 · IEEE Transactions on Systems Man and Cybernetics Systems
30. Dual regularized policy updating and shiftpoint detection for automated deployment of reinforcement learning controllers on industrial mechatronic systems
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31. Domain adaptation-based transfer learning using adversarial networks
    Farzaneh Shoeleh, Mohammad Mehdi Yadollahi, Masoud Asadpour · 2020 · The Knowledge Engineering Review
32. Boltzmann Distributed Replicator Dynamics: Population Games in a Microgrid Context
    Gustavo Alonso Chica Pedraza, Eduardo Mojica‐Nava, Ernesto Cadena Muñoz · 2021 · Games
33. Algorithmically-designed reward shaping for multiagent reinforcement learning in navigation
    Ifrah Saeed, Andrew C. Cullen, Zainab Zaidi, Sarah Erfani, Tansu Alpcan · 2025 · Neurocomputing
34. Multi-task transfer learning for seismic response prediction across steel and concrete moment-resisting frames
    Zhengyang Hou, Tian You, Wei Wang, Meiyu Du · 2025 · Soil Dynamics and Earthquake Engineering
35. Enabling Multi-Agent Transfer Reinforcement Learning via Scenario Independent Representation
    Ayesha Siddika Nipu, Siming Liu, Anthony Harris · 2023 · IEEE Conference on Games (CoG)
36. Optimized Transfer Learning For Wireless Channel Selection
    Mohammad Askarizadeh, Mostafa Hussien, Masoumeh Zare, Kim Khoa Nguyen · 2021 · Globecom
37. Knowledge Transfer-Based Multiagent Q-Learning for Medium Access in Dense Cellular Networks
    Kyungseop Shin, Hyun-Ho Choi, Howon Lee · 2022 · IEEE Wireless Communications Letters
38. An efficient technique to predict DC characteristics of nano-FinFETs using a deep neural network
    Qamar-Ud-Din Memon, Usama Munir, Umer Farooq Ahmed, M. Mansoor Ahmed · 2022 · Journal of Computational Electronics
39. Automaton-Guided Curriculum Generation for Reinforcement Learning Agents
    Yash Shukla, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov · 2023 · Proceedings of the International Conference on Automated Planning and Scheduling
40. Language model-accelerated deep symbolic optimization
    Felipe Leno da Silva, André Ricardo Gonçalves, Sam Nguyen, Denis Vashchenko, Ruben Glatt, Thomas Desautels, Mikel Landajuela, Daniel Faissol, Brenden K. Petersen · 2023 · Neural Computing and Applications
41. Interpersonal trust modelling through multi-agent Reinforcement Learning
    Vincent Frey, Julian Martinez · 2023 · Cognitive Systems Research
42. A lightweight gesture recognition network
    Guojinzhao Guo, Lei Xue-mei, Libo Li · 2024 · Journal of Visual Communication and Image Representation
43. Exploiting abstractions for grammar‐based learning of complex multi‐agent behaviours
    Dilini Samarasinghe, Michael Barlow, Erandi Lakshika, Kathryn Kasmarik · 2021 · International Journal of Intelligent Systems
44. Formation control of swarm robotics: A survey from biological inspirations to design automation methods
    Wenji Li, Zhaojun Wang, Chaotao Guan, Chuangbin Chen, Boxi Wang, Pengxiang Ren, Yifeng Qiu, Qinchang Zhang, Haoyu Wang, Dongliang Wang et al. · 2025 · Robotics and Autonomous Systems
45. Multi-missile coordinated penetration strategy based on hierarchical reinforcement learning in reduced space
    Yaoluo HUI, X M Li, Liang Chen, Zenghui Zhang, Jianing YAN · 2024 · Chinese Journal of Aeronautics
46. Enhancing Vehicular Network Security, Privacy, and Trust Through Reinforcement Learning: A Comprehensive Survey
    Elham Mohammadzadeh Mianji, Gabriel‐Miro Muntean, Irina Tal · 2025 · IEEE Transactions on Intelligent Transportation Systems
47. Double deep multiagent reinforcement learning for autonomous driving in traffic maps with road segments and unsignaled intersections
    Christos Spatharis, Konstantinos Blekas · 2020 · IEEE International Conference on Intelligent Transportation Systems (ITSC)
48. A REVIEW OF TRANSFER LEARNING: ADVANTAGES, STRATEGIES AND TYPES
    Oğuzhan Topsakal, Tahir Çetin Akıncı · 2023 · International Conference on Modern and Advanced Research (ICMAR)
49. Evaluating the stealth of reinforcement learning-based cyber attacks against unknown scenarios using knowledge transfer techniques
    Antonio Horta, Anderson Fernandes Pereira dos Santos, Ronaldo Ribeiro Goldschmidt · 2024 · Journal of Computer Security
50. Transfer Learning With Less Negative Transfer for Multi-Agent Reinforcement Learning: Application and Evaluation in Base Station Control
    Masanobu Namiki, Yoshihiro Okawa, Natsuki Morita, Jun Kakuta, Masatoshi Ogawa · 2024 · IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
51. S$$^{2}$$ES: a stationary and scalable knowledge transfer approach for multiagent reinforcement learning
    Tonghao Wang, Xingguang Peng, Demin Xu · 2021 · Complex & Intelligent Systems
52. Virtual Power Plant Adjustable Resource Aggregation Adjustment Optimization Strategy Based on Multi-agent Game
    Lingyan Que, Xuedong Jiang, Bo Wang, Xueqi Jin, Zhenhua Cai, Liqin Shi, Qingmin Lyn · 2021 · International Conference on Networking, Communications and Information Technology (NetCIT)
53. The Stochastic Augmented Lagrangian method for domain adaptation
    Zhanhong Jiang, Chao Liu, Young M. Lee, C. Hegde, S. Sarkar, Dong-Xiang Jiang · 2021 · Knowledge-Based Systems
54. Poisoning Attack for Inter-agent Transfer Learning
    Zelei Cheng, Zuotian Li · 2021 · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
55. Benchmarking a Decentralized Reinforcement Learning Control Strategy for an Energy Community
    Niklas Ebell, Marco Pruckner · 2021 · IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
56. Bayesian Deep Multi-Agent Multimodal Reinforcement Learning for Embedded Systems in Games, Natural Language Processing and Robotics
    Ioannis Kourouklides · 2022 · OSF Preprints (OSF Preprints)
57. RETRACTED: Improved Image Classification Algorithm Based on Convolutional Neural Network
    Xin Li, Luyu Dong, Mengting Li · 2021 · OALib · Retracted
58. Improving scalability of multi-agent deep reinforcement learning with suboptimal human knowledge
    Dingbang Liu, Fenghui Ren, Jun Yan, Guoxin Su, Wen Gu, Shohei Kato · 2026 · Autonomous Agents and Multi-Agent Systems
59. Learning to play against any mixture of opponents
    Max Smith, Thomas Anthony, Michael P. Wellman · 2023 · Frontiers in Artificial Intelligence
60. Automatic Transfer Rate Adjustment for Transfer Reinforcement Learning
    Hitoshi Kono, Yuto Sakamoto, Yonghoon Ji, Hiromitsu Fujii · 2020 · International Journal of Artificial Intelligence & Applications
61. Efficiently tracking multi-strategic opponents: A context-aware Bayesian policy reuse approach
    Hao Chen, Quan Liu, Jian Xin Huang, Ke Fu · 2022 · Applied Soft Computing
62. Knowledge transfer in multi-objective multi-agent reinforcement learning via generalized policy improvement
    Vicente de Almeida, Lucas N. Alegre, Ana L. C. Bazzan · 2023 · Computer Science and Information Systems
63. Evaluating the Effectiveness and Transferability of a Data-Driven Two-Region Perimeter Control Method Using Microsimulation
    Dongqin Zhou, Vikash V. Gayah · 2024 · Transportation Research Record Journal of the Transportation Research Board
64. Improved Learning in Multi-Agent Pursuer-Evader UAV Scenarios via Mechanism Design and Deep Reinforcement Learning
    Kléber Cabral, Jean-Alexis Delamer, Camille Alain Rabbath, Nicolas Lechevin, Craig Williams, Sidney Nascimento Givigi · 2024 · International Conference on Unmanned Aircraft Systems (ICUAS)
65. Accelerated Transfer Learning for Cooperative Transportation Formation Change via SDPA-MAPPO (Scaled Dot Product Attention-Multi-Agent Proximal Policy Optimization)
    Almira Budiyanto, Keisuke Azetsu, Nobutomo Matsunaga · 2024 · Automation
66. Intelligent multicast routing method based on multi-agent deep reinforcement learning in SDWN
    Hongwen Hu, Miao Ye, Chenwei Zhao, Qiuxiang Jiang, Xingsi Xue · 2023 · Mathematical Biosciences & Engineering
67. Learning Adaptation and Generalization from Human-Inspired Meta-Reinforcement Learning Using Bayesian Knowledge and Analysis
    Joshua Ho, Chien‐Min Wang, Chung‐Ta King, Yi-Hsin You, Chi-Wei Feng, Yen-Min Chen, Bo-Yi Kuo · 2023 · IEEE International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)
68. Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learning
    Ruo-Ze Liu, Haifeng Guo, Xiaozhong Ji, Yang Yu, Zhen-Jia Pang, Zitai Xiao, Yuzhou Wu, Tong Lü · 2019 · arXiv (Cornell University)
69. Transferring experiences in k-nearest neighbors based multiagent reinforcement learning: an application to traffic signal control
    Ana L. C. Bazzan, Vicente Nejar de Almeida, Monireh Abdoos · 2023 · AI Communications
70. Hybrid knowledge transfer for MARL based on action advising and experience sharing
    Feng Liu, Dongqi Li, Jian Gao · 2024 · Frontiers in Neurorobotics
71. Towards Zero-Shot Cross-Agent Transfer Learning Via Latent-Space Universal Notice Network
    Samuel Beaussant, Sébastien Lengagne, Benoît Thuilot, Olivier Stasse · 2024 · Robotics and Autonomous Systems
72. A new Reinforcement Learning based for Energy-efficient Multi-channel Data Gathering in Wireless Sensor Networks
    Mohamed Sahraoui, Azeddine Bilami · 2020 · International Symposium Informatics and its Applications
73. Optimized Transfer Learning: Application for Wireless Channel Selection
    Mohammad Askarizadeh, Mostafa Hussien, Masoumeh Zare, Kim Khoa Nguyen · 2021 · International Conference on Network and Service Management (CNSM)
74. Application of Reinforcement Learning in Multiagent Intelligent Decision-Making
    Xiaoyu Han · 2022 · Computational Intelligence and Neuroscience
75. Scaling Collaborative Space Networks with Deep Multi-Agent Reinforcement Learning
    Ricky Ma, Gabe Hernandez, Carrie Hernandez · 2023 · IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW)
76. Selective policy transfer in multi-agent systems with sparse interactions
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77. Large-Scale Urban Traffic Management Using Zero-Shot Knowledge Transfer in Multi-Agent Reinforcement Learning for Intersection Patterns
    Theodore Tranos, Christos Spatharis, Konstantinos Blekas, Andreas Stafylopatis · 2024 · Robotics
78. ATA-MAOPT: Multi-Agent Online Policy Transfer Using Attention Mechanism With Time Abstraction
    Chao Wang, Xiangbin Zhu · 2024 · IEEE Access
79. Multi-Agent Network Randomization Method for Robust Knowledge Transfer in Deep Multi-Agent Reinforcement Learning
    Dohyun Kim, Hoseong Jung, Jungho Bae · 2024 · International Conference on Control, Automation and Systems (ICCAS)
80. A Survey on Transfer Reinforcement Learning
    Jiaye Wei, Yixing Lan, Tao Tang, Tenglong Liu · 2025 · International Conference on Advanced Algorithms and Control Engineering (ICAACE)
81. Heuristics, Answer Set Programming and Markov Decision Process for Solving a Set of Spatial Puzzles*
    Thiago Freitas dos Santos, Paulo Eduardo Santos, Leonardo A. Ferreira, Reinaldo A. C. Bianchi, Pedro Cabalar · 2021 · Applied Intelligence
82. Oil Identification on Beaches Using Deep Learning Techniques
    Ramoni Reus Barros Negreiros, Rafael Araújo Dos Santos, André Luíz Firmino Alves, Anderson Almeida Firmino · 2020 · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
83. A Cooperative Multi-Agent Learning Approach for Avoiding DRDoS Attack
    Tomoki Kawazoe, Naoki Fukuta · 2021 · IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)
84. Vehicle Simulation Algorithm for Observations with Variable Dimensions Based on Deep Reinforcement Learning
    Yunzhuo Liu, Ruoning Zhang, Shijie Zhou · 2023 · Electronics
85. Overview on reinforcement learning of multi-agent game
    Wenrui Zou · 2023 · Journal of Physics Conference Series
86. Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games
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87. Methods and algorithms for knowledge reuse in multiagent reinforcement learning.
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88. Deep Q-Network Based Multi-agent Reinforcement Learning with Binary Action Agents
    Abdul Mueed Hafiz, G. Mohiuddin Bhat · 2020 · arXiv (Cornell University)
89. Temporal Inconsistency-Based Intrinsic Reward for Multi-Agent Reinforcement Learning
    Shaoqi Sun, Kele Xu · 2023 · International Joint Conference on Neural Networks (IJCNN)
90. Knowledge Injection for Multiagent Systems via Counterfactual Perception Shaping
    Nicholas Zerbel, Kagan Tumer · 2023 · Frontiers in artificial intelligence and applications
91. Leaders and Collaborators: Addressing Sparse Reward Challenges in Multi-Agent Reinforcement Learning
    Shaoqi Sun, Hui Liu, Kele Xu, Bo Ding · 2024 · IEEE Transactions on Emerging Topics in Computational Intelligence
92. Career planning and pathway generation based on multimodal learning analytics
    Wenqing Liu · 2025 · International Journal of Information and Communication Technology
93. Engineering Inter-agent Explainability in BDI Agents
    Katharine Beaumont, Elena Yan, Samuele Burattini, Rem Collier · 2025 · Lecture notes in computer science
94. Transfer learning-based method for data-driven seismic response prediction of steel moment resisting frames with different stories
    Zhengyang Hou, Tian You, Wei Wang, Shiye Wang · 2025 · Journal of Building Engineering
95. Fuzzy Knowledge-Based Hierarchical Reinforcement Learning for Large-Scale Heterogeneous Multiagent Systems
    Dingbang Liu, Fenghui Ren, Jun Yan, Guoxin Su, Wen Gu, Shōhei Kato · 2025 · IEEE Transactions on Cybernetics
96. Transfer Reinforcement Learning for Resource Allocation in Mobile Edge Computing Systems: A Survey
    Chenhao Ni, Xiangjie Kong, Jiaxin Du, Guojiang Shen, Wail Al-Asad, Geyong Min · 2026 · IEEE Transactions on Services Computing
97. Rethinking the Utilization of Individual Rewards in Multiagent Reinforcement Learning With Sparse Team Rewards
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98. Enhancing Red Team Agent Learning with the Kill Chain Catalyst Algorithm in Capture the Flag Scenarios
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99. Агентно-ориентированная интеллектуальная система поддержки принятия решений: архитектура и разработка
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100. CLASSIFICATION OF MULTI-AGENT REINFORCEMENT LEARNING PROBLEMS
     Vyacheslav Ivanovich Petrenko, V.I. PETRENKO · 2021 · News of the Kabardin-Balkar Scientific Center of RAS