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    Active robot learning for building up high-order beliefs

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    Authors
    Li, Dayou
    Liu, Beisheng
    Maple, Carsten
    Jiang, Daming
    Yue, Yong
    Issue Date
    2008
    Subjects
    active learning
    cognitive robotics
    fuzzy logic
    
    Metadata
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    Abstract
    High-order beliefs of service robots regard the robots' thought about their users' intention and preference. The existing approaches to the development of such beliefs through machine learning rely on particular social cues or specifically defined award functions. Their applications can, therefore, be limited. This paper presents an active robot learning approach to facilitate the robots to develop the beliefs by actively collecting/discovering evidence they need. The emphasis is on active learning. Hence social cues and award functions are not necessary. Simulations show that the presented approach successfully enabled a robot to discover evidences it needs.
    Citation
    Dayou Li; Beisheng Liu; Maple, C.; Daming Jiang; Yong Yue; (2008) Active Robot Learning for Building Up High-Order Beliefs, Fuzzy Systems and Knowledge Discovery, FSKD '08, Fifth International Conference on , vol.3, pp.201-205
    Publisher
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
    URI
    http://hdl.handle.net/10547/270600
    DOI
    10.1109/FSKD.2008.186
    Additional Links
    http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4666240
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9780769533056
    ae974a485f413a2113503eed53cd6c53
    10.1109/FSKD.2008.186
    Scopus Count
    Collections
    Centre for Research in Distributed Technologies (CREDIT)

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