Supervised learning plays a key role in the operation of many biological and artificial neural
networks. Analysis of the computations underlying supervised learning is facilitated by the …

Abstract Models are among the most essential tools in robotics, such as kinematics and
dynamics models of the robot's own body and controllable external objects. It is widely …

Joining the ancient debate over the roles of reason and appetite in the moral mind, In Praise
of Desire takes the side of appetite. Acting for moral reasons, acting in a praiseworthy …

Shortly after John Eccles completed his studies of synaptic inhibition in the spinal cord, for
which he was awarded the 1963 Nobel Prize in physiology/medicine, he opened another …

A coordinated movement is easy to recognize, but we know little about how it is achieved. In
search of the neural basis of coordination, we present a model of spinocerebellar …

Initial investigations of the cerebellar microcircuit inspired the Marr–Albus theoretical
framework of cerebellar function. We review recent developments in the experimental …

We present an approach to learn inverse kinematics of redundant systems without prior-or
expert-knowledge. The method allows for an iterative bootstrapping and refinement of the …

The brain needs to predict how the body reacts to motor commands, but how a network of
spiking neurons can learn non-linear body dynamics using local, online and stable learning …

The human motor system can rapidly adapt its motor output in response to errors. The
prevailing theory of this process posits that the motor system adapts an internal forward …

We conducted a literature review on sensor heads for humanoid robots. A strong case is
made on topics involved in human robot interaction. Having found that vision is the most …