This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
This case study demonstrates how the synthesis and the analysis of minimal recurrent neural robot control provide insights into the exploration of embodiment. By using structural e...
Prediction of dynamic features is an important task for determining the manipulation strategies of an object. This paper presents a technique for predicting dynamics of objects re...
Shun Nishide, Tetsuya Ogata, Jun Tani, Kazunori Ko...
In this paper we present an approach to robot arm control based on exploiting the dynamical properties of a simple neural network oscillator circuit coupled to the joints of an ar...