ICDL 2026 - 3rd Edition
at Kyoto University, Kyoto, Japan
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Call for Papers
In pursuit of fostering insightful conversation on the subject of learning, particularly at the intersection of Cognitive Architectures and Developmental AI, we invite participants to submit their contributions.
Beyond submitting papers presenting state-of-the-art research, we invite authors to share works in progress, reports featuring preliminary results, and critical reflections and position papers. This inclusive approach allows for exploring and identifying pertinent and novel discussion points that authors may wish to address during the ensuing panel discussions.
Important Dates
Important Dates
Submission Deadline: July 31, 2026.
Notification of Acceptance: August 14*, 2026.
Camera-ready: August 28, 2026.
Workshop date and time: September 15, 2026 - 13:45-17:05
Registration deadline: TBA.
*Submissions will be reviewed progressively as they are received, following a first-come-first-served basis, to guarantee enough time for early contributors to plan their trip to the conference.
Submission Procedure
Submission Procedure
Submission format: Extended abstract (2 to 4 pages) or a short position paper (1 page) - Page limit excluding references.
File format: PDF.
Templates: Standard RAS IEEE two-column paper templates, to be used for all submission types. Please refer to the available LaTeX or Word templates.
The submitted contribution must be written in English and does not need to be anonymized (single-blind review process). A panel of experts from relevant fields will be asked to review the contributions. Accepted papers will be invited for presentation either in oral or poster format, and the paper will be uploaded to the workshop website.
Please submit your contribution on the AI-CogDev forms.
For any questions, please contact us at aicogdev.workshop@gmail.com
Keynote Speakers
Matej Hoffmann
Matej Hoffmann
Czech Technical University
Understanding infant development through baby humanoid robots
Human newborns are at first virtually helpless, but within a year or two they learn to effectively control their bodies, to reach and to locomote. What brain algorithms are at the basis of this learning? Current knowledge on sensorimotor development is patchy. A common but unverified idea is that learning involves intrinsically motivated exploration of the body and the world, giving rise to coherent internal representations that subsequently allow effective motor control. In this talk, I will question these assumptions.
We longitudinally follow infants in three different scenarios - spontaneous behavior, reaching for tactile stimuli on the body, and reaching for objects presented visually - and use behavioral data from these three contexts to: (i) identify signatures of active exploration and goal-orientedness in spontaneous behavior, (ii) compare reaching to somatosensory and visual targets over development to understand the interplay of target localization and motor control.
To shed light on the mechanisms of the development of the "sensorimotor self", we instantiate these scenarios in baby humanoid robots. I will also show AI tools that we develop to extract infant 3D pose from videos, reattribute motion data to robots, and replay the motor, proprioceptive, visual, and tactile experience of infants.
Biography
Biography
Matej Hoffmann received the Ph.D. degree in Informatics from Artificial Intelligence Lab, University of Zurich, Zurich, Switzerland, in 2012. From 2013 to 2016, he conducted postdoctoral research with the iCub Facility of the Italian Institute of Technology, Genoa, Italy, supported by a Marie Curie Intra-European Fellowship. In 2017, he joined the Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, where he is currently an Associate Professor and Head of the Humanoid and Cognitive Robotics Group. His research interests include humanoid and cognitive developmental robotics and development of the "sensorimotor self".
Francisco Cruz
Francisco Cruz
UNSW Sydney
TBA
TBA
Biography
Biography
Francisco received a bachelor's degree in engineering and a master's degree in computer engineering from the University of Santiago, Chile, in 2004 and 2006, respectively, and a PhD degree from the University of Hamburg, Germany, in 2017, working in developmental robotics focused on interactive reinforcement learning. In 2015, he was a Visiting Researcher at the Emergent Robotics Laboratory, Osaka University, and in 2018, a Visiting Researcher at the Polytechnic School, University of Pernambuco, Brazil. Francisco is a Senior Lecturer in Cognitive Robotics at UNSW Sydney since 2022, where he leads the Autonomous Agents and Robotics Research (A2R2) group. His current research interests include reinforcement learning, explainable artificial intelligence, human-robot interaction, artificial neural networks, and psychologically and bio-inspired models.
Vieri Giuliano Santucci
Vieri Giuliano Santucci
TBA
TBA
TBA
Biography
Biography
TBA
Program
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