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cs.AI2025
Expandable Decision-Making States for Multi-Agent Deep Reinforcement Learning in Soccer Tactical Analysis
Kenjiro Ide, Taiga Someya, Kohei Kawaguchi +1
Invasion team sports such as soccer produce a high-dimensional, strongly coupled state space as many players continuously interact on a shared field, challenging quantitative tacti…
cs.AI2025
Interpretable Low-Dimensional Modeling of Spatiotemporal Agent States for Decision Making in Football Tactics
Kenjiro Ide, Taiga Someya, Kohei Kawaguchi +1
Understanding football tactics is crucial for managers and analysts. Previous research has proposed models based on spatial and kinematic equations, but these are computationally e…