Multi-agent Reinforcement Learning
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Benchmarks
Most implemented
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
The StarCraft Multi-Agent Challenge
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning
Value-Decomposition Networks For Cooperative Multi-Agent Learning
Papers
DRG-MAPPO: Hierarchical Dynamic Role-Graph Multi-Agent Reinforcement Learning for Cooperative Air Combat
Multi-Agent Reinforcement Learning (MARL) has emerged as a pivotal paradigm for complex decision-making in autonomous systems and air combat. While MARL has demonstrated significant potential in air combat, achieving sop…
Multi-agent Reinforcement LearningMulti-Agent Reinforcement Learning for Autonomous UAV Exploration in Wildfire Response
This study develops a deep reinforcement learning framework for training Unmanned Aerial Vehicle (UAV) agents to navigate and monitor simulated wildfire environments. Results show that agents learn increasingly stable an…
Multi-agent Reinforcement LearningOnline Change-point Detection for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) systems rely on past experience for learning coordinated behaviour, but this experience may become unreliable if the environment or task objective changes during trai…
Multi-agent Reinforcement LearningLow-Altitude Fluid Antenna Network with Multi-Agent Reinforcement Learning
Low-altitude wireless networks (LAWNs) integrate terrestrial and aerial platforms to provide ubiquitous communication, sensing, and localization services for unmanned aerial vehicles (UAVs) and electric vertical takeoff …
Multi-agent Reinforcement LearningTransfer LearningAI agents in Algorithmic Electricity Markets: On the Emergence of Tacit Collusion
As electricity market participants increasingly adopt learning-based agents for their bidding strategies, electricity markets are becoming algorithmic. Evidence from algorithmic markets in other domains shows that tacit …
Multi-agent Reinforcement LearningSIGMA: Structured Noise-Effect-Aware Grouped Multi-Agent Aggregation
Cooperative multi-agent reinforcement learning (MARL) faces significant challenges in maintaining robust coordination under noisy observations. Although observation disturbances are often introduced independently across …
Multi-agent Reinforcement LearningStarcraft II