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.

Source: Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports

Papers

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Showing 351–360 of 1718 papers

Title	Date	Tasks	Status	Score
Learning to Solve the Min-Max Mixed-Shelves Picker-Routing Problem via Hierarchical and Parallel Decoding	Feb 14, 2025	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	5
Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning	Feb 14, 2023	Multi-agent Reinforcement Learning	CodeCode Available	5
Learning Transferable Cooperative Behavior in Multi-Agent Teams	Jun 4, 2019	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	5
Data sharing games	Jan 26, 2021	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Learning with Opponent-Learning Awareness	Sep 13, 2017	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	5
Learning to Schedule Communication in Multi-agent Reinforcement Learning	Feb 5, 2019	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	5
Adaptive trajectory-constrained exploration strategy for deep reinforcement learning	Dec 27, 2023	Deep Reinforcement LearningMuJoCo	CodeCode Available	5
Learning to Gather without Communication	Feb 21, 2018	Multi-agent Reinforcement LearningPosition	CodeCode Available	5
Learning to Share and Hide Intentions using Information Regularization	Aug 6, 2018	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Curriculum learning for multilevel budgeted combinatorial problems	Jul 7, 2020	Combinatorial OptimizationMulti-agent Reinforcement Learning	CodeCode Available	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