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 91–100 of 1718 papers

Title	Date	Tasks	Status	Hype
Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing	Feb 7, 2024	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Settling Decentralized Multi-Agent Coordinated Exploration by Novelty Sharing	Feb 3, 2024	Multi-agent Reinforcement Learning	CodeCode Available	1
Context-aware Communication for Multi-agent Reinforcement Learning	Dec 25, 2023	Multi-agent Reinforcement LearningQuantization	CodeCode Available	1
Multi-Agent Reinforcement Learning via Distributed MPC as a Function Approximator	Dec 8, 2023	Model Predictive ControlMulti-agent Reinforcement Learning	CodeCode Available	1
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization	Nov 3, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning	Nov 1, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Multi-Agent Reinforcement Learning-Based UAV Pathfinding for Obstacle Avoidance in Stochastic Environment	Oct 25, 2023	Model Predictive ControlMulti-agent Reinforcement Learning	CodeCode Available	1
Theory of Mind for Multi-Agent Collaboration via Large Language Models	Oct 16, 2023	HallucinationMulti-agent Reinforcement Learning	CodeCode Available	1
Self-Supervised Neuron Segmentation with Multi-Agent Reinforcement Learning	Oct 6, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
Effective Multi-Agent Deep Reinforcement Learning Control with Relative Entropy Regularization	Sep 26, 2023	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available	1

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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