Adaptive interactive device control by using reinforcement learning in ambient information environment
نویسندگان
چکیده
In ambient information systems, not only extracting human behavior by sensor network but also adaptive autonomous interaction between the environment and humans is an important function. In this paper we propose a reinforcement learning framework to extract suitable interaction for each person from daily behavior. In the experiment, we show the feasibility of the proposed methodology. Keywords-interaction sequence; reinforcement learning; profit-sharing; ambient information system
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