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Learning Finite-State Machine Controllers From Motion Capture Data
2009
IEEE Transactions on Computational Intelligence and AI in Games
With characters in computer games and interactive media increasingly being based on real actors, the individuality of an actor's performance should not only be reflected in the appearance and animation of the character but also in the Artificial Intelligence that governs the character's behavior and interactions with the environment. Machine learning methods applied to motion capture data provide a way of doing this. This paper presents a method for learning the parameters of a Finite State
doi:10.1109/tciaig.2009.2019630
fatcat:dduinsn65zhlxk27rlusio7nj4