—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
In this paper, we present an algorithm based on the GRASP metaheuristic for solving a dynamic assignment problem in a P2P network designed for sending real-time video over the Int...
Prediction is an important task in robot motor control where it is used to gain feedback for a controller. With such a self-generated feedback, which is available before sensor rea...
This paper introduces a distributed haptic control architecture that can render direct interaction between users in addition to cooperative manipulation of virtual objects. The pr...