— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
My research focus is on using continuous state partially observable Markov decision processes (POMDPs) to perform object manipulation tasks using a robotic arm. During object mani...
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
Akihiko Yamaguchi, Jun Takamatsu, Tsukasa Ogasawar...
In this paper we describe MRSCL Geometry a collaborative educational activity that explores the use of robotic technology and wirelessly connected Pocket PCs as tools for teaching ...