Critic-based Learning of Actions with Self-Organising Feature Maps
نویسندگان
چکیده
In this paper we develop a mechanism for critic-based learning in continuous state and action spaces. Our approach is based on the Motoric Map model [RMS90], by which we wish to overcome the restrictions of traditional Reinforcement Learning methods concerning continuous spaces. Covariance Learning is introduced as algorithm to determine the best possible action for a given state using the critic's reward information. We will discuss first results regarding Covariance Learning and also apply it to on-line learning scenarios.
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تاریخ انتشار 1996