We propose an approach to building topological maps of environments based on image sequences. The central idea is to use manifold constraints to find representative feature protot...
In online tracking, the tracker evolves to reflect variations in object appearance and surroundings. This updating process is formulated as a supervised learning problem, thus a ...
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
In this paper, we propose a serving system consisting intelligent agents processing society information in a multi-user domain. The agents use the similarity information on the us...
Policy Reuse is a method to improve reinforcement learning with the ability to solve multiple tasks by building upon past problem solving experience, as accumulated in a Policy Li...