Motivation

This special session focuses on self-organizing clustering for continual learning emerging from adaptation, learning, and cognitive development through interaction with people and dynamic environments from the conceptual, theoretical, methodological, and technical points of view. This session welcomes fundamental research on self-organizing clustering algorithms. In addition, the session also welcomes research on applied topics relating to exploiting knowledge with intelligent applications/robots.

Keywords

Self-organizing Clustering, Topological Clustering, Continual Learning, Knowledge Extraction

Organizers

Yuichiro Toda, Okayama University
Naoki Masuyama, Osaka Metropolitan University
Seiki Ubukata, Osaka Metropolitan University
Takeru Aoki, Tokyo University of Science
Chin Wei Hong, Tokyo Metropolitan University

Important Dates

Paper submission: January 15, 2024
Notification of acceptance: March 15, 2024
Final paper submission: May 1, 2024