SOTAVerified

SMAC

Bechmarks for Efficient Exploration of Completion of Multi-stage Tasks and Usage of Environmental Factors

Papers

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Showing 1–10 of 121 papers

TitleStatusHype
Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic GenerationCode0
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement LearningCode1
Ensemble-MIX: Enhancing Sample Efficiency in Multi-Agent RL Using Ensemble Methods—0
Dynamic Sight Range Selection in Multi-Agent Reinforcement Learning—0
POCAII: Parameter Optimization with Conscious Allocation using Iterative Intelligence—0
JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 MinutesCode1
Rainbow Delay Compensation: A Multi-Agent Reinforcement Learning Framework for Mitigating Delayed Observation—0
Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent CooperationCode0
AVA: Attentive VLM Agent for Mastering StarCraft IICode1
Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning—0
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All datasetsSMAC MMM2SMAC 3s5z_vs_3s6zSMAC corridorSMAC 6h_vs_8zSMAC 27m_vs_30mSMAC 26m_vs_30mSMAC 3s5z_vs_4s6zSMAC 6h_vs_9zSMAC corridor_2z_vs_24zgSMAC MMM2_7m2M1M_vs_8m4M1MSMAC MMM2_7m2M1M_vs_9m3M1M

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DDNAverage Score19.45—Unverified
2DPLEXAverage Score19.4—Unverified
3DMIXAverage Score19.33—Unverified
4QPLEXAverage Score19.06—Unverified
5QMIXAverage Score19.01—Unverified
6VDNAverage Score17.3—Unverified