Model-Based Reinforcement Learning

Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience

Generalizing the operation of robots in dynamical environments regardless of the task complexity is one of the ultimate goals of robotics researchers. Learning from demonstration approaches supported by transfer learning and user feedback offer a remarkable solution to achieve generalization …

Mehmet Ege Cansev, Honghu Xue, Nils Rottmann, Adna Bliek, Luke E Miller, Elmar Rueckert, Philipp Beckerle

Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience

Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks

In this paper, we propose learning a predictor model that allows simulated rollouts in a rank-based black-box optimizer Covariance Matrix Adaptation Evolutional Strategy (CMA-ES) to achieve higher sample-efficiency. …

Honghu Xue, Sven Böttger, Nils Rottmann, Harit Pandya, Ralf Bruder, Gerdhard Neumann, Achim Schweikard, Elmar Rueckert

Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks