Group Formation by Group Joining and Opinion Updates Via Multi-Agent Online Gradient Ascent [AI-eXplained]

Chuang Chieh Lin; Chih Chieh Hung; Chi Jen Lu; Po An Chen

doi:10.1109/MCI.2023.3304084

Group Formation by Group Joining and Opinion Updates Via Multi-Agent Online Gradient Ascent [AI-eXplained]

Chuang Chieh Lin
, Chih Chieh Hung^*
, Chi Jen Lu
, Po An Chen

^*Corresponding author for this work

Institute of Information Management

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	60-61
Number of pages	2
Journal	IEEE Computational Intelligence Magazine
Volume	18
Issue number	4
DOIs	https://doi.org/10.1109/MCI.2023.3304084
State	Published - 1 Nov 2023

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abstract = "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.",

author = "Lin, \{Chuang Chieh\} and Hung, \{Chih Chieh\} and Lu, \{Chi Jen\} and Chen, \{Po An\}",

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AU - Chen, Po An

PY - 2023/11/1

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Group Formation by Group Joining and Opinion Updates Via Multi-Agent Online Gradient Ascent [AI-eXplained]

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