淡江大學機構典藏:Item 987654321/124668
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    題名: Group Formation by Group Joining and Opinion Updates via Multi-Agent Online Gradient Ascent
    作者: Lin, Chuang-chieh
    關鍵詞: Nash equilibrium;Machine learning;Follow-the-regularized-Leader;Gradient ascent;Group formation
    日期: 2023-10-17
    上傳時間: 2023-10-23 12:05:24 (UTC+8)
    出版者: IEEE
    摘要: This article aims to exemplify best-response dynamics and multi-agent online learning by group formation. This extended abstract provides a summary of the full
    paper in IEEE Computational Intelligence Magazine on the special issue AI-eXplained (AI-X). The full paper
    includes interactive components to facilitate interested readers to grasp the idea of pure-strategy Nash equilibria and how the system of strategic agents
    converges to a stable state by the decentralized online gradient ascent with and without regularization.
    關聯: IEEE Computational Intelligence Magazine 18(4),　p.60-61
    DOI: 10.1109/MCI.2023.3304084
    顯示於類別:[資訊工程學系暨研究所] 期刊論文

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