Google Research Football
Emerging11papers using it
2022first seen
'Google Research Football' is a benchmark that contains a simulated football environment used to evaluate cooperative Multi-Agent Reinforcement Learning (MARL) algorithms.
Papers using Google Research Football (9)
- Adaptive Context Length Optimization with Low-Frequency Truncation for Multi-Agent Reinforcement LearningSPECTra: Scalable Multi-Agent Reinforcement Learning with
Permutation-Free NetworksAutonomous Partner Selection for Cooperative Multi-Agent Reinforcement LearningBridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent ConsensusMulti-Agent Deep Reinforcement Learning Under Constrained CommunicationsLAGMA: Latent Goal-guided Multi-agent Reinforcement LearningLearning to Collaborate by Grouping: a Consensus-oriented Strategy for
Multi-agent Reinforcement LearningPTDE: Personalized Training with Distilled Execution for Multi-Agent
Reinforcement LearningMulti-Task Multi-Agent Shared Layers are Universal Cognition of
Multi-Agent Coordination