We consider the problem of how the CNS learns to control dynamics of a mechanical system. By using a paradigm where a subject's hand interacts with a virtual mechanical envir...
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...
In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard probl...
This article describes a developmental system based on information theory implemented on a real robot that learns a model of its own sensory and actuator apparatus. There is no in...
Lars Olsson, Chrystopher L. Nehaniv, Daniel Polani
: - This paper addresses an inverse controller design for excitation system with changing parameters and nonsmooth nonlinearities in the actuator. The existence of such nonlinearit...