The motivation for this special session stems from the need to explore and advance the field of continual learning, a critical area in artificial intelligence that seeks to emulate the human ability to learn from experiences in an ongoing manner. The continual structuration of information and knowledge is essential for the development of intelligent systems capable of adapting to new environments, learning from their own experiences, and acquiring more complex knowledge over time. Our aim is to foster a deeper understanding of how continual learning can be achieved through self-organizing clustering, adaptation, and cognitive development in dynamic environments.
The objectives of this special session are to bring together researchers and practitioners to discuss novel approaches, methodologies, and applications in the field of continual learning, focusing particularly on self-organizing clustering algorithms. These algorithms have the potential to revolutionize the way intelligent systems are designed by allowing for more autonomous and adaptive learning processes. We aim to bridge theoretical foundations with real-world applications, thereby fostering interdisciplinary discussions and innovation.
This special session focuses on continual learning techniques for adaptive and autonomous systems in dynamic and complex environments. Continual learning, inspired by human cognitive processes, aims to equip intelligent systems with the ability to incrementally acquire, refine, and synthesize knowledge over time. The session seeks to bridge theoretical advancements and practical applications in artificial intelligence, fostering interdisciplinary discussions that integrate neural networks, fuzzy systems, and evolutionary computation with domains such as robotics and dynamic information systems.
We welcome the submission of high-quality papers that utilize self-organizing clustering algorithms and other computational intelligence techniques to address the challenges of continual learning in dynamic and complex environments.
Topics of interest include, but not limited to:
Please follow the submission guideline from the IJCNN 2025 Submission Website. Special session papers are treated the same as regular conference papers. Please specify that your paper is for the Special Session on Self-organizing Clustering for Continual Learning and its Applications. All the accepted and presented papers will be published on IEEE Xplore Digital Library and indexed by Scopus.
Assoc. Prof. Yuichiro Toda, Okayama University, Japan
Assoc. Prof. Naoki Masuyama, Osaka Metropolitan University, Japan
Prof. Chu Kiong Loo, University of Malaya, Malaysia
Prof. Stefan Wermter, University of Hamburg, Germany
Dr. Wei Shuing Liew, University of Malaya, Malaysia
Primary contact email address: ytoda(at)okayama-y.ac.jp (Yuichiro Toda)