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 15511575 of 1718 papers

TitleStatusHype
Revisiting Parameter Sharing in Multi-Agent Deep Reinforcement LearningCode0
SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement LearningCode0
Multi-Agent Quantum Reinforcement Learning using Evolutionary OptimizationCode0
Interpretable Emergent Language Using Inter-Agent TransformersCode0
Partially Observable Mean Field Multi-Agent Reinforcement Learning Based on Graph-AttentionCode0
A collaboration of multi-agent model using an interactive interfaceCode0
Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement LearningCode0
Enhancing Heterogeneous Multi-Agent Cooperation in Decentralized MARL via GNN-driven Intrinsic RewardsCode0
RLCard: A Toolkit for Reinforcement Learning in Card GamesCode0
Multi-Agent Reinforcement Learning: A Report on Challenges and ApproachesCode0
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum ChannelsCode0
Data sharing gamesCode0
Curriculum learning for multilevel budgeted combinatorial problemsCode0
A Distributed Approach to Autonomous Intersection Management via Multi-Agent Reinforcement LearningCode0
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) CompetitionCode0
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RLCode0
Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement LearningCode0
MAC-PO: Multi-Agent Experience Replay via Collective Priority OptimizationCode0
Independent Learning in Constrained Markov Potential GamesCode0
Multi-Agent Reinforcement Learning for Visibility-based Persistent MonitoringCode0
Communicating via Markov Decision ProcessesCode0
M^3RL: Mind-aware Multi-agent Management Reinforcement LearningCode0
Logic-based Reward Shaping for Multi-Agent Reinforcement LearningCode0
Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement LearningCode0
Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement LearningCode0
Show:102550
← PrevPage 63 of 69Next →

Benchmark Results

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