SvgAI - Training artificial intelligent agent to use SVG editor

Anh H. Dang, Wataru Kameyama

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

    Abstract

    Deep reinforcement learning has been successfully used to train artificial intelligent (AI) agents to outperform humans in many tasks as well as to enhance the capability in robotic automation. In this paper, we propose a framework to train an AI agent to use scalable vector graphic (SVG) editor to draw SVG images. Hence, the objective of this AI agent is to draw SVG images that are similar as much as possible to their target raster images. We find that it is crucial to distinguish the action space into two sets and apply a different exploration policy on each set during the training process. Evaluations show that our proposed dual-exploration policy greatly stabilizes the training process and increases the accuracy of the AI agent. SVG images produced by the proposed AI agent also have superior quality compared to popular raster-to-SVG conversion software.

    Original languageEnglish
    Title of host publicationIEEE 20th International Conference on Advanced Communication Technology
    Subtitle of host publicationOpening New Era of Intelligent Things, ICACT 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages132-138
    Number of pages7
    Volume2018-February
    ISBN (Electronic)9791188428007
    DOIs
    Publication statusPublished - 2018 Mar 23
    Event20th IEEE International Conference on Advanced Communication Technology, ICACT 2018 - Chuncheon, Korea, Republic of
    Duration: 2018 Feb 112018 Feb 14

    Other

    Other20th IEEE International Conference on Advanced Communication Technology, ICACT 2018
    CountryKorea, Republic of
    CityChuncheon
    Period18/2/1118/2/14

    Fingerprint

    Intelligent agents
    Reinforcement learning
    Robotics
    Automation

    Keywords

    • Exploration Policy
    • Q-Learning
    • Reinforcement Learning
    • SVG
    • SvgAI

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

    Cite this

    Dang, A. H., & Kameyama, W. (2018). SvgAI - Training artificial intelligent agent to use SVG editor. In IEEE 20th International Conference on Advanced Communication Technology: Opening New Era of Intelligent Things, ICACT 2018 (Vol. 2018-February, pp. 132-138). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ICACT.2018.8323672

    SvgAI - Training artificial intelligent agent to use SVG editor. / Dang, Anh H.; Kameyama, Wataru.

    IEEE 20th International Conference on Advanced Communication Technology: Opening New Era of Intelligent Things, ICACT 2018. Vol. 2018-February Institute of Electrical and Electronics Engineers Inc., 2018. p. 132-138.

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

    Dang, AH & Kameyama, W 2018, SvgAI - Training artificial intelligent agent to use SVG editor. in IEEE 20th International Conference on Advanced Communication Technology: Opening New Era of Intelligent Things, ICACT 2018. vol. 2018-February, Institute of Electrical and Electronics Engineers Inc., pp. 132-138, 20th IEEE International Conference on Advanced Communication Technology, ICACT 2018, Chuncheon, Korea, Republic of, 18/2/11. https://doi.org/10.23919/ICACT.2018.8323672
    Dang AH, Kameyama W. SvgAI - Training artificial intelligent agent to use SVG editor. In IEEE 20th International Conference on Advanced Communication Technology: Opening New Era of Intelligent Things, ICACT 2018. Vol. 2018-February. Institute of Electrical and Electronics Engineers Inc. 2018. p. 132-138 https://doi.org/10.23919/ICACT.2018.8323672
    Dang, Anh H. ; Kameyama, Wataru. / SvgAI - Training artificial intelligent agent to use SVG editor. IEEE 20th International Conference on Advanced Communication Technology: Opening New Era of Intelligent Things, ICACT 2018. Vol. 2018-February Institute of Electrical and Electronics Engineers Inc., 2018. pp. 132-138
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