Turn Based

Turn-based systems, characterized by alternating actions between agents, are being actively researched across diverse fields, from human-computer interaction to sports analytics and game AI. Current research focuses on improving the realism and efficiency of these systems, employing techniques like duplex models for real-time interaction, hierarchical imitation learning for behavior replication, and transformer networks for prediction and analysis in complex scenarios. These advancements are driving improvements in areas such as human-computer interaction, game design, and sports performance analysis, offering valuable insights into strategic decision-making and player behavior.