Recent years have seen a growing interest in using computational modeling to complement classic experimental approaches for studying infant development. This workshop is aimed at modelers and non-modelers alike. It showcases recent successes of the fruitful interaction of empirical and theoretical/computational research in infant development. Leading theorists will highlight how careful theoretical work can lead to a better understanding of empirical data and generate testable predictions for future experiments. A second aim of the workshop is to compare different modeling approaches or „schools“ including neural networks, Bayesian reasoning, and dynamical systems, emphasizing their respective strengths and weaknesses.
Participation of the workshop is free of charge. In order to register please use this link and follow the instructions.
The workshop will comprise a poster session. Participants can apply for a poster presentation within the above registration form.
Seating at the venue as well as poster boards are limited and registrations will be handled on a first come first serve basis.
|14:10||Keynote Gregor Schöner, University of Bochum:
Dynamical Systems Thinking: from metaphor to neural theory
|14:45||Keynote Verena V. Hafner, Humboldt University Berlin:
Sensorimotor learning and development in intelligent autonomous systems
|15:30||Keynote J. Kevin O'Regan, Université René Descartes Paris:
Deducing abstract concepts without knowing what you’re looking for -- the example of space
|15:55||Poster Presentations and Coffee Break|
|16:45||Keynote Hiroki Mori, Osaka University:
A synthetic approach toward fetal development: Can whole body fetal simulation lead to new insights for human development studies?
|17:20||Keynote Denis Mareschal, Birkbeck, University of London:
Connectionist models of infant learning development