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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.

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Papers

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Showing 151–200 of 1718 papers

TitleStatusHype
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style TransferCode1
Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy OptimizationCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
Laser Learning Environment: A new environment for coordination-critical multi-agent tasksCode1
Cooperative Policy Learning with Pre-trained Heterogeneous Observation RepresentationsCode1
Learning Fair Policies in Decentralized Cooperative 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
Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized IntersectionsCode1
Lenient Multi-Agent Deep Reinforcement LearningCode1
Randomized Entity-wise Factorization for Multi-Agent Reinforcement LearningCode1
Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative ExplorationCode1
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight DeliveryCode1
Decentralized Social Navigation with Non-Cooperative Robots via Bi-Level OptimizationCode1
Collaborating with Humans without Human DataCode1
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningCode1
CoLight: Learning Network-level Cooperation for Traffic Signal ControlCode1
FACMAC: Factored Multi-Agent Centralised Policy GradientsCode1
Collaborative Visual NavigationCode1
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive EnvironmentsCode1
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team CompositionCode1
Actor-Attention-Critic for Multi-Agent Reinforcement LearningCode1
ALMA: Hierarchical Learning for Composite Multi-Agent TasksCode1
Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement LearningCode1
JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 MinutesCode1
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?Code1
MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal ControlCode1
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?Code1
Is Machine Learning Ready for Traffic Engineering Optimization?Code1
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory ManagementCode1
CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy ManagementCode1
Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language ModelsCode1
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural NetworkCode1
Multi-Agent Constrained Policy OptimisationCode1
Effective and Stable Role-Based Multi-Agent Collaboration by Structural Information PrinciplesCode1
Effective control of two-dimensional Rayleigh--Bénard convection: invariant multi-agent reinforcement learning is all you needCode1
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement LearningCode1
Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement LearningCode1
Bayesian Action Decoder for Deep Multi-Agent Reinforcement LearningCode1
Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement LearningCode1
Information Design in Multi-Agent Reinforcement LearningCode1
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement LearningCode1
Energy-based Surprise Minimization for Multi-Agent Value FactorizationCode1
Interaction Pattern Disentangling for Multi-Agent Reinforcement LearningCode1
Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial ExplorationCode1
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam SearchCode1
A multi-agent reinforcement learning model of common-pool resource appropriationCode1
Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement LearningCode1
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement LearningCode1
Celebrating Diversity in Shared Multi-Agent Reinforcement LearningCode1
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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