Google Research Football

Google Research Football (GRF) is a simulated soccer environment used to advance research in multi-agent reinforcement learning (MARL) and related machine learning techniques. Current research focuses on developing sophisticated models, including transformers, graph neural networks, and convolutional neural networks, to improve agent performance in increasingly complex scenarios (e.g., 11-vs-11 matches), often incorporating techniques like reward shaping and active learning to enhance training efficiency and strategy diversity. This research contributes to a deeper understanding of MARL algorithms and their application to complex, dynamic systems, with potential implications for sports analytics, game AI, and broader applications of AI in strategic decision-making.