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

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Showing 251–300 of 1718 papers

TitleStatusHype
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team CompositionCode1
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online AdvertisingCode1
Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement LearningCode1
CoLight: Learning Network-level Cooperation for Traffic Signal ControlCode1
Cooperation and Fairness in Multi-Agent Reinforcement LearningCode1
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-LearningCode1
Distributed Resource Allocation with Multi-Agent Deep Reinforcement Learning for 5G-V2V CommunicationCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight DeliveryCode1
FACMAC: Factored Multi-Agent Centralised Policy GradientsCode1
Collaborative Visual NavigationCode1
Decentralized Social Navigation with Non-Cooperative Robots via Bi-Level OptimizationCode1
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningCode1
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement LearningCode1
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement LearningCode1
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler MitigationCode1
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics NetworkCode1
Effective and Stable Role-Based Multi-Agent Collaboration by Structural Information PrinciplesCode1
Effective Multi-Agent Deep Reinforcement Learning Control with Relative Entropy RegularizationCode1
Collaborating with Humans without Human DataCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial ExplorationCode1
Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learningCode1
Communicative Reinforcement Learning Agents for Landmark Detection in Brain ImagesCode1
Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement LearningCode1
Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-agent Deep Reinforcement Learning ApproachCode1
Fully Decentralized Multi-Agent Reinforcement Learning with Networked AgentsCode1
Learning Scalable Multi-Agent Coordination by Spatial Differentiation for Traffic Signal ControlCode1
Dashing for the Golden Snitch: Multi-Drone Time-Optimal Motion Planning with Multi-Agent Reinforcement LearningCode1
HAD-Gen: Human-like and Diverse Driving Behavior Modeling for Controllable Scenario GenerationCode1
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive EnvironmentsCode1
Energy-based Surprise Minimization for Multi-Agent Value FactorizationCode1
Rethinking the Implementation Matters in Cooperative Multi-Agent Reinforcement LearningCode1
Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language ModelsCode1
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARLCode1
Interaction Pattern Disentangling for Multi-Agent Reinforcement LearningCode1
Mean Field Multi-Agent Reinforcement LearningCode1
PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape EstimationCode1
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?Code1
Breaking the Curse of Dimensionality in Multiagent State Space: A Unified Agent Permutation Framework—0
Coding for Distributed Multi-Agent Reinforcement Learning—0
An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning—0
Anytime PSRO for Two-Player Zero-Sum Games—0
AoI-Aware Resource Allocation for Platoon-Based C-V2X Networks via Multi-Agent Multi-Task Reinforcement Learning—0
Age Minimization in Massive IoT via UAV Swarm: A Multi-agent Reinforcement Learning Approach—0
ClusterComm: Discrete Communication in Decentralized MARL using Internal Representation Clustering—0
Cluster-Based Multi-Agent Task Scheduling for Space-Air-Ground Integrated Networks—0
Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning—0
Credit Assignment with Meta-Policy Gradient for Multi-Agent Reinforcement Learning—0
Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MATD3final agent reward-14—Unverified
#ModelMetricClaimedVerifiedStatus
1DRIMAMedian Win Rate15—Unverified
#ModelMetricClaimedVerifiedStatus
1Fusion-Multi-Actor-Attention-CriticAverage Reward39—Unverified