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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 431–440 of 1718 papers

Title	Date	Tasks	Status	Score
Convergent Policy Optimization for Safe Reinforcement Learning	Oct 26, 2019	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning	Oct 31, 2022	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Health-Informed Policy Gradients for Multi-Agent Reinforcement Learning	Aug 2, 2019	Multi-agent Reinforcement LearningPolicy Gradient Methods	CodeCode Available	5
Quantum Computing and Neuromorphic Computing for Safe, Reliable, and explainable Multi-Agent Reinforcement Learning: Optimal Control in Autonomous Robotics	Jul 29, 2024	Multi-agent Reinforcement Learning	CodeCode Available	5
Heterogeneous Multi-Agent Reinforcement Learning via Mirror Descent Policy Optimization	Aug 13, 2023	LEMMAMuJoCo	CodeCode Available	5
HARP: Human-Assisted Regrouping with Permutation Invariant Critic for Multi-Agent Reinforcement Learning	Sep 18, 2024	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	5
Heterogeneous Multi-agent Zero-Shot Coordination by Coevolution	Aug 9, 2022	Multi-agent Reinforcement Learning	CodeCode Available	5
GOV-REK: Governed Reward Engineering Kernels for Designing Robust Multi-Agent Reinforcement Learning Systems	Apr 1, 2024	Multi-agent Reinforcement Learning	CodeCode Available	5
Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning	Jun 2, 2023	Multi-agent Reinforcement Learning	CodeCode Available	5
GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning	Mar 2, 2023	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available	5

Show:10 25 50

← PrevPage 44 of 172Next →

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