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 1301–1350 of 1718 papers

TitleStatusHype
Multi-agent reinforcement learning strategy to maximize the lifetime of Wireless Rechargeable—0
Multi-Agent Reinforcement Learning via Adaptive Kalman Temporal Difference and Successor Representation—0
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization—0
Major-Minor Mean Field Multi-Agent Reinforcement Learning—0
Multi-agent Reinforcement Learning with Sparse Interactions by Negotiation and Knowledge Transfer—0
Multi-Agent Reinforcement Learning with Shared Resource in Inventory Management—0
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management—0
Multi-Agent Reinforcement Learning with Common Policy for Antenna Tilt Optimization—0
Safety-Aware Multi-Agent Learning for Dynamic Network Bridging—0
Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing—0
Multi-Agent Reinforcement Learning with Selective State-Space Models—0
Multi-Agent Reinforcement Learning with a Hierarchy of Reward Machines—0
Multi-agent Reinforcement Learning with Deep Networks for Diverse Q-Vectors—0
BGC: Multi-Agent Group Belief with Graph Clustering—0
Multi-Agent Reinforcement Learning with Graph Convolutional Neural Networks for optimal Bidding Strategies of Generation Units in Electricity Markets—0
Multi-agent Reinforcement Learning with Graph Q-Networks for Antenna Tuning—0
Multi-Agent Reinforcement Learning with Multi-Step Generative Models—0
Multi-Agent RL-Based Industrial AIGC Service Offloading over Wireless Edge Networks—0
Emergent Social Learning via Multi-agent Reinforcement Learning—0
Multi-Agent Transfer Learning via Temporal Contrastive Learning—0
Multi-agent transformer-accelerated RL for satisfaction of STL specifications—0
Multi-Agent Vulnerability Discovery for Autonomous Driving with Hazard Arbitration Reward—0
Multimodal Query Suggestion with Multi-Agent Reinforcement Learning from Human Feedback—0
Multi-Objective Optimization of the Textile Manufacturing Process Using Deep-Q-Network Based Multi-Agent Reinforcement Learning—0
Multi-Objective Optimization Using Adaptive Distributed Reinforcement Learning—0
MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning—0
Multi-Robot Collaboration through Reinforcement Learning and Abstract Simulation—0
Learning Multi-Robot Decentralized Macro-Action-Based Policies via a Centralized Q-Net—0
Multi-Robot Formation Control Using Reinforcement Learning—0
Multi-Robot Path Planning Combining Heuristics and Multi-Agent Reinforcement Learning—0
Multi-robot Social-aware Cooperative Planning in Pedestrian Environments Using Multi-agent Reinforcement Learning—0
Multi-Scenario Combination Based on Multi-Agent Reinforcement Learning to Optimize the Advertising Recommendation System—0
Multi-source Plume Tracing via Multi-Agent Reinforcement Learning—0
Multi-Target Active Object Tracking with Monte Carlo Tree Search and Target Motion Modeling—0
Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning—0
Online Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning—0
Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approach—0
Mutation-Bias Learning in Games—0
Muti-Agent Proximal Policy Optimization For Data Freshness in UAV-assisted Networks—0
Nash Soft Actor-Critic LEO Satellite Handover Management Algorithm for Flying Vehicles—0
Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator—0
Navigating the Smog: A Cooperative Multi-Agent RL for Accurate Air Pollution Mapping through Data Assimilation—0
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints—0
Negotiated Reasoning: On Provably Addressing Relative Over-Generalization—0
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning—0
Networked Agents in the Dark: Team Value Learning under Partial Observability—0
Networked Multi-Agent Reinforcement Learning with Emergent Communication—0
Peer-to-Peer Energy Trading of Solar and Energy Storage: A Networked Multiagent Reinforcement Learning Approach—0
Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning—0
The impact of behavioral diversity in multi-agent 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