Supporting ProjectsThe APERoC workshop is supported by two European projects that both focus on learning from sensorimotor experience.
eSMCsWhile the majority of current robot architectures is based on a "perception-then-action" control strategy, the eSMCs project adopts a theoretical perspective that turns this classical view upside-down and emphasizes the constitutive role of action for perception. The key concept our project is based on is that of sensorimotor contingencies, that is, law-like relations between actions and associated changes in sensory input. We will advance this concept further and suggest that actions not only play a key role for perception, but also in developing more complex cognitive capabilities. We suggest that extended sensorimotor contingencies (eSMCs) may be exploited for the definition of object concepts and action plans and that their mastery can lead to goal-oriented behaviour.
The project pursues the following objectives: We will employ this approach to establish computational models that are suitable as controllers for autonomous robots; we will implement these eSMCs-based models on robotic platforms with different sensor-actuator equipment; we will investigate learning and adaptivity of eSMCs in artificial systems, focussing on sensorimotor interactions, object recognition and action planning; we will investigate and validate the concept of eSMCs in natural cognitive systems, by carrying out behavioural and neurophysiological studies on healthy human subjects; finally, we will test predictions derived from this concept in patients with movement dysfunctions, where ensuing changes in perceptual and cognitive processing will be tested. A set of benchmarks and task scenarios will be developed serving as demonstrators for the enhanced performance of artificial systems based on the eSMCs approach. Moreover, the usefulness of the approach for the development of applications in augmenting human behaviour will be demonstrated.
The project is funded by the European Union under the grant no. 270212. More information can be found on the website.
XperienceThe core idea behind Xperience is the use of Structural Bootstrapping, an idea developed to explain child language acquisition, to rapidly acquire new knowledge about concepts, words, or actions, for use by humanoid robots, based on existing knowledge. Structural bootstrapping is a new learning method that makes use of two different kinds of information about concepts, words or actions to speed up learning. Specifically, structural bootstrapping leverages information about how concepts, words, or actions are used (their syntax) against the concept, word, or action’s meaning (its semantics) to learn new concepts, words, and actions. In Xperience, the idea of structural bootstrapping will be used across different level of cognitive domain including low-level sensorimotor reasoning and high-level symbolic reasoning. The project will show that solutions found for one problem can be transferred to similar domains.
The project is funded by the European Union under the grant no. 270273 More information can be found on the website.