The embodiment stance postulates that cognition cannot be understood as long as the links between cognitive processes and the sensory and motor surfaces are left unexamined. An understanding of cognition must also reflect that cognition takes place in organisms or agents who are situated in structured environments to which their bodies and nervous systems are specifically adapted.
Creating robotic demonstrations of cognitive process models is a powerful way to establish that principles of embodiment are addressed. In fact, the links to sensory and motor surfaces and immersion in the environment are difficult to probe without real-world robotic implementations.
In robotics, the behavior-based approach has similarly emphasized direct links to simple sensory and motor systems. For roboticists, the challenge has consisted of scaling such systems up toward true cognition, including finding ways of how to enrich such systems with representations.
Neuronal dynamics provides a a powerful theoretical language that may address both goals. It is based on neural principles, but also enables robotic implementation through simple interfaces with sensory and motor systems.
An obstacle to the wide-spread use of neuronal dynamics as a theoretical framework by both researchers in embodied cognition and in autonomous robotics is the seeming mathematical sophistication required to make use of these concepts. This school provides a hands-on and down-to-earth introduction to neuronal dynamics ideas and enables participants to become productive within this framework.