| Group Formation by Group Joining and Opinion Updates via Multi-Agent Online Gradient Ascent | |
|---|---|
| 學年 | 112 |
| 學期 | 1 |
| 出版（發表）日期 | 2023-10-17 |
| 作品名稱 | Group Formation by Group Joining and Opinion Updates via Multi-Agent Online Gradient Ascent |
| 作品名稱（其他語言） | |
| 著者 | Chuang-Chieh Lin, Chih-Chieh Hung, Chi-Jen Lu, and Po-An Chen |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | IEEE Computational Intelligence Magazine 18(4), p.60-61 |
| 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. |
| 關鍵字 | Nash equilibrium;Machine learning;Follow-the-regularized-Leader;Gradient ascent;Group formation |
| 語言 | en_US |
| ISSN | 1556-6048; 1556-603X |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | Hung, Chih-chieh |
| 審稿制度 | 是 |
| 國別 | USA |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/124668 ) |
| SDGS | 優質教育 |
GoogleAnalytics