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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/37594

    Title: Constructing an intelligent behavior avatar in a virtual world: a self-learning model based on reinforcement
    Authors: Chen, Jui-fa;Lin, Wei-chuan;Bai, Hua-sheng;Yang, Chia-che;Chao, Hsiao-chuan
    Contributors: 淡江大學資訊工程學系
    Date: 2005-08
    Issue Date: 2010-04-15 10:21:11 (UTC+8)
    Publisher: Institute of electrical and electronics engineers (IEEE)
    Abstract: In this paper, a novel method for personal intelligent behavior avatar (IBA) is proposed to acquire autonomous behavior based on the interactions between user and smart objects in the virtual environment. In this method, the behavior decision model and the self-learning model are integrated by Bayesian networks and reinforcement learning. The Bayesian networks can treat interaction experiences using statistical processes, and the sureness of decision making is represented by certainty factors using stochastic reasoning. The reinforcement learning is implemented by learning experimentation or trial and error mechanisms to improve the performance of IBA through feedback. Therefore, the IBA makes a strategic decision that is approximated and appropriate to the user through the self-learning process by reinforcement learning. Finally, the feasibility of this method is investigated by imitating user's behavior and the results of self-learning process. The results of simulation show that the method is successful in imitating user's behavior and improving the performance of IBA.
    Relation: Information Reuse and Integration, Conf, 2005. IRI -2005 IEEE International Conference on, pp.421-426
    DOI: 10.1109/IRI-05.2005.1506510
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

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