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References (66)

[1]
Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning
2025Sunwoo Lee, Jaebak Hwang et al.
[2]
SMAC-Hard: Enabling Mixed Opponent Strategy Script and Self-play on SMAC
2024Yue Deng, Yan Yu et al.
[3]
RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space
2024Jingdi Chen, Hanhan Zhou et al.
[4]
HyperComm: Hypergraph-based communication in multi-agent reinforcement learning
2024Tianyu Zhu, Xinli Shi et al.
[5]
Learning Multi-Agent Communication from Graph Modeling Perspective
2024Shengchao Hu, Li Shen et al.
[6]
T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration
2024Chuxiong Sun, Zehua Zang et al.
[7]
The Dormant Neuron Phenomenon in Multi-Agent Reinforcement Learning Value Factorization
2024Haoyuan Qin, Chennan Ma et al.
[8]
Sample-Efficient Multiagent Reinforcement Learning with Reset Replay
2024Yaodong Yang, Guangyong Chen et al.
[9]
Context-aware Communication for Multi-agent Reinforcement Learning
2023Xinran Li, Jun Zhang
[10]
ConcaveQ: Non-Monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning
2023Huiqun Li, Hanhan Zhou et al.
[11]
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization
2023Siqi Shen, Chennan Ma et al.
[12]
FoX: Formation-aware exploration in multi-agent reinforcement learning
2023Yonghyeon Jo, Sunwoo Lee et al.
[13]
MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning
2023Tianmeng Hu, Biao Luo et al.
[14]
Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackers
2023Lei Yuan, Zifei Zhang et al.
[15]
NA2Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning
2023Zichuan Liu, Zichuan Liu et al.
[16]
Effective and Stable Role-Based Multi-Agent Collaboration by Structural Information Principles
2023Xianghua Zeng, Hao-Lun Peng et al.
[17]
Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey
2023James Orr, Ayan Dutta
[18]
Complementary Attention for Multi-Agent Reinforcement Learning
2023Jianzhun Shao, Hongchang Zhang et al.
[19]
Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning
2023Yifan Zang, Jinmin He et al.
[20]
RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution
2023Pengyi Li, Jianye Hao et al.

Showing 20 of 66 references

Founder's Pitch

"Develop a reinforcement learning framework to improve adaptability in multi-agent systems using successive sub-value functions."

Reinforcement LearningScore: 6View PDF ↗

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5

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10

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2.5

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