Multi-agent Reinforcement Learning

The target of Multi-agent Reinforcement Learning is to solve complex problems by integrating multiple agents that focus on different sub-tasks. In general, there are two types of multi-agent systems: independent and cooperative systems.

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Papers

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Showing 261–270 of 1718 papers

Title	Date	Tasks	Status	Hype	Score
MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning	Jun 5, 2021	Atari GamesCPU	CodeCode Available	1	5
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning	May 23, 2024	DiversityMulti-agent Reinforcement Learning	CodeCode Available	1	5
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network	Mar 2, 2019	Combinatorial OptimizationManagement	CodeCode Available	1	5
Collaborating with Humans without Human Data	Oct 15, 2021	Multi-agent Reinforcement Learning	CodeCode Available	1	5
Mava: a research library for distributed multi-agent reinforcement learning in JAX	Jul 3, 2021	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	1	5
Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images	Aug 18, 2020	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
marl-jax: Multi-Agent Reinforcement Leaning Framework	Mar 24, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit Assignment	May 21, 2021	counterfactualMulti-agent Reinforcement Learning	CodeCode Available	1	5
Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement	Nov 2, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
Negative Update Intervals in Deep Multi-Agent Reinforcement Learning	Sep 13, 2018	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	1	5

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All datasets ParticleEnvs Cooperative Communication SMAC-Exp UAV Logistics

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MATD3	final agent reward	-14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRIMA	Median Win Rate	15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Fusion-Multi-Actor-Attention-Critic	Average Reward	39	—	Unverified