A reinforcement-learning pipeline for predicting macro-actions in Honor of Kings improves action prediction accuracy, but the method is imitation of human replay labels, not the claimed environmental interaction.
Font and Tobias Mahlmann
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Think in Games: Learning to Reason in Games via Reinforcement Learning with Large Language Models
A reinforcement-learning pipeline for predicting macro-actions in Honor of Kings improves action prediction accuracy, but the method is imitation of human replay labels, not the claimed environmental interaction.