Cognitive Development and Symbol Emergence

Special Section name:

Scope

Humans develop their cognitive systems through physical and social interactions with their environment. They also organize symbol systems, including language, that enable communication and cooperation with others. These two processes are referred to as cognitive development and symbol emergence, respectively. Modeling and understanding these phenomena using a constructive/synthetic approach is important not only for developing lifelong learning autonomous robots, i.e., embodied artificial general intelligence, but also for understanding human cognitive systems. Despite the remarkable progress in AI and robotics, there is still considerable room for contributions in this area.

This section aims to elucidate the interrelated processes of cognitive development and symbol emergence in robotics. By providing a platform for interdisciplinary research exchange, we aim to advance the field of cognitive robotics and deepen our understanding of human cognition and symbolic representation.

Cognitive development involves the process of adaptation of robots' cognitive abilities over time, including learning from interactions. Symbol emergence focuses on the creation of symbols and symbolic systems through robots' interactions with their environment, addressing the need for meaningful, grounded symbols for communication and reasoning.

We invite contributions from a variety of disciplines, including robotics, AI, cognitive science, developmental psychology, linguistics, and neuroscience. By fostering interdisciplinary dialogue, we aim to push the boundaries of cognitive development and symbol emergence to advance the creation of intelligent, adaptive, and human-like robotic systems.

Keywords

Cognitive Development,
Cognitive Robotics,
Developmental Robotics,
Cognitive and Developmental Systems,
Symbol Emergence,
Symbol Grounding,
Symbolic Representation,
Symbolic Systems,
Language Acquisition,
Embodied Cognition,
Sensorimotor/Multimodal Learning,
Human-like Cognitive Systems,
Social Interaction,
Human-Robot Interaction,
Symbolic Interaction,
Lifelong/Open-ended Learning,
Intrinsic Motivation,
Machine Learning,
Deep Learning,
Representation Learning,
Predictive Coding,
Free-Energy Principle,
Active Inference and Exploration,
World Models,
Probabilistic Generative Models,
Neuro/Brain-Inspired Cognitive Systems

List of Section Editors

[Section Chief Editor]
Tadahiro Taniguchi, Professor, College of Information Science and Engineering, Ritsumeikan University, Japan, taniguchi@em.ci.ritsumei.ac.jp

[Section Vice Chief Editor]
Yukie Nagai, International Research Center for Neurointelligence, The University of Tokyo, Japan, nagai.yukie@mail.u-tokyo.ac.jp

[Section Editor]
Alessandra Sciutti, Italian Institute of Technology *
Akira Taniguchi, Ritsumeikan University *
Angelo Cangelosi, University of Manchester
Britta Wrede, Bielefeld University
Chen Yu, University of Texas at Austin
Chie Hieida, Nara Institute of Science and Technology
Emre Ugur, Boğaziçi University *
Erhan Oztop, Özyeğin University / Osaka University
Friederike Eyssel, Bielefeld University
Hiroyuki Izuka, Hokkaido University
Jochen Triesch, Frankfurt Institute for Advanced Studies, Goethe University Frankfurt
Jun Tani, OIST
Kento Kawaharazuka, The University of Tokyo
Lorenzo Jamone, Queen Mary University of London
Masahiro Suzuki, The University of Tokyo *
Pablo Lanillos, Donders Institute for Brain Cognition and Behaviour, Nijmege
Pierre-yves Oudeyer, French Institute for Research in Computer Science and Automation (INRIA)
Reiji Suzuki, Nagoya University
Shingo Murata, Keio University *
Tadahiro Taniguchi, Ritumeikan University
Takato Horii, Osaka University *
Takayuki Nagai, Osaka University
Tatsuya Matsushima, The University of Tokyo
Tetsuya Ogata, Waseda University
Tomoaki Nakamura, University of Electro-Communications

Note that editors with (*) have the initial responsibility for handling submissions. Authors submitting contributed papers can suggest associate editors from editors with (*), and reviewers from all editors and possible reviewers outside the list.

[Advisor]
Minoru Asada, Osaka University / International Professional University of Technology in Osaka
Giulio Sandini, Italian Institute of Technology

Additional information

The following papers are closely related to the special section.

Tadahiro Taniguchi, Emre Ugur, Matej Hoffmann, Lorenzo Jamone, Takayuki Nagai, Benjamin Rosman, Toshihiko Matsuka, Naoto Iwahashi, Erhan Oztop, Justus Piater, Florentin Wörgötter. "Symbol Emergence in Cognitive Developmental Systems: A Survey." IEEE Transactions on Cognitive and Developmental Systems, 11(4), 494-516, 2018.
Yukie Nagai. "Predictive learning: its key role in early cognitive development." Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1771):20180030, 2019.
Karl Friston, Rosalyn J. Moran, Yukie Nagai, Tadahiro Taniguchi, Hiroaki Gomi, Josh Tenenbaum. "World model learning and inference." Neural Networks, 144, 573-590, 2021.
Tadahiro Taniguchi, Shingo Murata, Masanori Suzuki, Daniele Ognibene, Pablo Lanillos, Emre Uğur, Lorenzo Jamone, Tomoaki Nakamura, Alberto Ciria, Boris Lara, Giovanni Pezzulo. "World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges." Advanced Robotics, 13, 780-806, 2023.
Tadahiro Taniguchi, Takayuki Nagai, Tomoaki Nakamura, Naoto Iwahashi, Tetsuya Ogata, Hideki Asoh. "Symbol Emergence in Robotics: A Survey." Advanced Robotics, 30(11-12), 706-728, 2016.

External website

For more information about the special section, visit the following URL.

https://ss-ar.emergent-symbol.systems/