1

End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments
We solve a pedestrian visual navigation problem with a first-person view in an urban setting via deep reinforcement learning in an end-to-end manner …
Honghu Xue, Rui Song, Julian Petzold, Benedikt Hein, Heiko Hamann, Elmar Rueckert
PDF Cite Video DOI
End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments
ACNMP: Skill transfer and task extrapolation through learning from demonstration and reinforcement learning via representation sharing
To equip robots with dexterous skills, an effective approach is to first transfer the desired skill via Learning from Demonstration (LfD), then let the robot improve it …
M. Tuluhan Akbulut, Erhan Oztop, M. Yunus Seker, Honghu Xue, Ahmet E. Tekden, Emre Ugur
PDF Cite Code
ACNMP: Skill transfer and task extrapolation through learning from demonstration and reinforcement learning via representation sharing
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
PDF Cite Code Video Source Document
Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks