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 151–200 of 1718 papers

TitleStatusHype
Efficient Multi-agent Reinforcement Learning by PlanningCode1
Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy OptimizationCode1
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningCode1
Energy-based Surprise Minimization for Multi-Agent Value FactorizationCode1
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement LearningCode1
Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learningCode1
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-NCode1
A Sustainable Ecosystem through Emergent Cooperation in Multi-Agent Reinforcement LearningCode1
Actor-Attention-Critic for Multi-Agent Reinforcement LearningCode1
Formal Contracts Mitigate Social Dilemmas in Multi-Agent RLCode1
Randomized Entity-wise Factorization for Multi-Agent Reinforcement LearningCode1
Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative ExplorationCode1
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler MitigationCode1
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight DeliveryCode1
Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority InfluenceCode1
Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement LearningCode1
Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement LearningCode1
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARLCode1
Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement LearningCode1
Inequity aversion improves cooperation in intertemporal social dilemmasCode1
Interaction Pattern Disentangling for Multi-Agent Reinforcement LearningCode1
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style TransferCode1
ALMA: Hierarchical Learning for Composite Multi-Agent TasksCode1
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement LearningCode1
Cooperative Policy Learning with Pre-trained Heterogeneous Observation RepresentationsCode1
JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 MinutesCode1
Language Instructed Reinforcement Learning for Human-AI CoordinationCode1
Laser Learning Environment: A new environment for coordination-critical multi-agent tasksCode1
A MARL Based Multi-Target Tracking Algorithm Under Jamming Against RadarCode1
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory ManagementCode1
Learning Individually Inferred Communication for Multi-Agent CooperationCode1
Learning Multi-Agent Communication through Structured Attentive ReasoningCode1
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural NetworkCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
Learning to Share in Multi-Agent Reinforcement LearningCode1
Learning to Simulate Self-Driven Particles System with Coordinated Policy OptimizationCode1
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement LearningCode1
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground with Human-in-the-loopCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
MA2CL:Masked Attentive Contrastive Learning for Multi-Agent Reinforcement LearningCode1
Context-aware Communication for Multi-agent Reinforcement LearningCode1
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement LearningCode1
Communicative Reinforcement Learning Agents for Landmark Detection in Brain ImagesCode1
Mava: a research library for distributed multi-agent reinforcement learning in JAXCode1
Contrastive Identity-Aware Learning for Multi-Agent Value DecompositionCode1
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam SearchCode1
A multi-agent reinforcement learning model of common-pool resource appropriationCode1
Collaborating with Humans without Human DataCode1
CoLight: Learning Network-level Cooperation for Traffic Signal ControlCode1
Collaborative Visual NavigationCode1
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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