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A Dynamic Neural Network Approach to Generating Robot's Novel Actions: A Simulation Experiment
https://oist.repo.nii.ac.jp/records/1307
https://oist.repo.nii.ac.jp/records/13072fc84122-2114-4a47-b7b5-e2836581c5b7
名前 / ファイル | ライセンス | アクション |
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UR_cameraReady_20180515 (644.8 kB)
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2020-03-18 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | A Dynamic Neural Network Approach to Generating Robot's Novel Actions: A Simulation Experiment | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
資源タイプ | conference paper | |||||
著者 |
Hwang, Jungsik
× Hwang, Jungsik× Tani, Jun |
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書誌情報 |
en : 2018 15th International Conference on Ubiquitous Robots p. 355-361, 発行日 2018-08-23 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In this study, we investigate how a robot can generate novel and creative actions from its own experience of learning basic actions. Inspired by a machine learning approach to computational creativity, we propose a dynamic neural network model that can learn and generate robot's actions. We conducted a set of simulation experiments with a humanoid robot. The results showed that the proposed model was able to learn the basic actions and also to generate novel actions by modulating and combining those learned actions. The analysis on the neural activities illustrated that the ability to generate creative actions emerged from the model's nonlinear memory structure self-organized during training. The results also showed that the different way of learning the basic actions induced the self-organization of the memory structure with the different characteristics, resulting in the generation of different levels of creative actions. Our approach can be utilized in human-robot interaction in which a user can interactively explore the robot's memory to control its behavior and also discover other novel actions. | |||||
出版者 | ||||||
出版者 | IEEE | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | info:doi/10.1109/URAI.2018.8441824 | |||||
権利 | ||||||
権利情報 | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||
関連サイト | ||||||
識別子タイプ | URI | |||||
関連識別子 | https://ieeexplore.ieee.org/document/8441824 | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa |