— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
Axel Rottmann, Christian Plagemann, Peter Hilgers,...
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
This paper deals with the adaptive variance scaling issue in continuous Estimation of Distribution Algorithms. A phenomenon is discovered that current adaptive variance scaling me...
We propose a framework to reconstruct human motion based on monocular camera video and motion database. In this framework, we use silhouettes for rough motion estimation based on a...