Open-end human robot interaction from the dynamical systems perspective: Mutual adaptation and incremental learning

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    11 Citations (Scopus)

    Abstract

    This paper describes interactive learning between human subjects and robot using the dynamical systems approach. Our research concentrated on the navigation system of a humanoid robot and human subjects whose eyes were covered. We used the recurrent neural network (RNN) for the robot control. We used a "consolidation-learning algorithm" as a model of hippocampus in brain. In this method, the RNN was trained by both a new data and the rehearsal outputs of the RNN, not to damage the contents of current memory. The proposed method enabled the robot to improve the performance even when learning continued for a long time (open-end). The dynamical systems analysis of RNNs supports these differences.

    Original languageEnglish
    Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
    EditorsB. Orchard, C. Yang, M. Ali
    Pages435-444
    Number of pages10
    Volume3029
    Publication statusPublished - 2004
    Event17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2004 - Ottowa, Ont., Canada
    Duration: 2004 May 172004 May 20

    Other

    Other17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2004
    CountryCanada
    CityOttowa, Ont.
    Period04/5/1704/5/20

    Fingerprint

    Human robot interaction
    Recurrent neural networks
    Dynamical systems
    Robots
    Navigation systems
    Consolidation
    Learning algorithms
    Brain
    Systems analysis
    Data storage equipment

    ASJC Scopus subject areas

    • Hardware and Architecture

    Cite this

    Ogata, T., Sugano, S., & Tani, J. (2004). Open-end human robot interaction from the dynamical systems perspective: Mutual adaptation and incremental learning. In B. Orchard, C. Yang, & M. Ali (Eds.), Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3029, pp. 435-444)

    Open-end human robot interaction from the dynamical systems perspective : Mutual adaptation and incremental learning. / Ogata, Tetsuya; Sugano, Shigeki; Tani, Jun.

    Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). ed. / B. Orchard; C. Yang; M. Ali. Vol. 3029 2004. p. 435-444.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Ogata, T, Sugano, S & Tani, J 2004, Open-end human robot interaction from the dynamical systems perspective: Mutual adaptation and incremental learning. in B Orchard, C Yang & M Ali (eds), Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). vol. 3029, pp. 435-444, 17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2004, Ottowa, Ont., Canada, 04/5/17.
    Ogata T, Sugano S, Tani J. Open-end human robot interaction from the dynamical systems perspective: Mutual adaptation and incremental learning. In Orchard B, Yang C, Ali M, editors, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). Vol. 3029. 2004. p. 435-444
    Ogata, Tetsuya ; Sugano, Shigeki ; Tani, Jun. / Open-end human robot interaction from the dynamical systems perspective : Mutual adaptation and incremental learning. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). editor / B. Orchard ; C. Yang ; M. Ali. Vol. 3029 2004. pp. 435-444
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