SOTAVerified

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

Showing 5175 of 1718 papers

TitleStatusHype
CoLight: Learning Network-level Cooperation for Traffic Signal ControlCode1
Effective control of two-dimensional Rayleigh--Bénard convection: invariant multi-agent reinforcement learning is all you needCode1
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive EnvironmentsCode1
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTSCode1
A coevolutionary approach to deep multi-agent reinforcement learningCode1
FACMAC: Factored Multi-Agent Centralised Policy GradientsCode1
Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language ModelsCode1
CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy ManagementCode1
A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal ControlCode1
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learningCode1
A Game-Theoretic Approach to Multi-Agent Trust Region OptimizationCode1
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online AdvertisingCode1
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-LearningCode1
Celebrating Diversity in Shared Multi-Agent Reinforcement LearningCode1
CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement LearningCode1
Collaborating with Humans without Human DataCode1
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam SearchCode1
Simplified Action Decoder for Deep Multi-Agent Reinforcement LearningCode1
CAMP: Collaborative Attention Model with Profiles for Vehicle Routing ProblemsCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
Effective Multi-Agent Deep Reinforcement Learning Control with Relative Entropy RegularizationCode1
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural NetworkCode1
Dashing for the Golden Snitch: Multi-Drone Time-Optimal Motion Planning with Multi-Agent Reinforcement LearningCode1
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground with Human-in-the-loopCode1
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler MitigationCode1
Show:102550
← PrevPage 3 of 69Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MATD3final agent reward-14Unverified
#ModelMetricClaimedVerifiedStatus
1DRIMAMedian Win Rate15Unverified
#ModelMetricClaimedVerifiedStatus
1Fusion-Multi-Actor-Attention-CriticAverage Reward39Unverified