CLASSQ-L: A Q-Learning Algorithm for Adversarial Real-Time Strategy Games
نویسندگان
چکیده
We present CLASSQ-L (for: class Q-learning) an application of the Q-learning reinforcement learning algorithm to play complete Wargus games. Wargus is a real-time strategy game where players control armies consisting of units of different classes (e.g., archers, knights). CLASSQ-L uses a single table for each class of unit so that each unit is controlled and updates its class’ Qtable. This enables rapid learning as in Wargus there are many units of the same class. We present initial results of CLASSQ-L against a variety of opponents.
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تاریخ انتشار 2012