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 251–260 of 1718 papers

Title	Date	Tasks	Status	Hype	Score
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement Learning	Mar 16, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1	5
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising	Jun 11, 2021	Multi-agent Reinforcement Learning	CodeCode Available	1	5
Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement Learning	Oct 8, 2024	GSM8KMulti-agent Reinforcement Learning	CodeCode Available	1	5
CoLight: Learning Network-level Cooperation for Traffic Signal Control	May 11, 2019	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	1	5
MA2CL:Masked Attentive Contrastive Learning for Multi-Agent Reinforcement Learning	Jun 3, 2023	Contrastive LearningMulti-agent Reinforcement Learning	CodeCode Available	1	5
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer	Jun 20, 2022	Multi-agent Reinforcement LearningQ-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
Contrastive Identity-Aware Learning for Multi-Agent Value Decomposition	Nov 23, 2022	Contrastive LearningDiversity	CodeCode Available	1	5
Context-aware Communication for Multi-agent Reinforcement Learning	Dec 25, 2023	Multi-agent Reinforcement LearningQuantization	CodeCode Available	1	5
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks	Oct 27, 2021	Multi-agent Reinforcement Learningreinforcement-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