Using Parameterized Black-Box Priors to Scale Up Model-Based Policy Search for Robotics

20 September 2017

Papers citing "Using Parameterized Black-Box Priors to Scale Up Model-Based Policy Search for Robotics"

10 / 10 papers shown

Title
RegHEC: Hand-Eye Calibration via Simultaneous Multi-view Point Clouds Registration of Arbitrary Object Shiyu Xing Fengshui Jing M. Tan 17 1 0 27 Apr 2023
Learning of Parameters in Behavior Trees for Movement Skills Matthias Mayr Konstantinos Chatzilygeroudis Faseeh Ahmad Luigi Nardi Volker Krueger OffRL 21 20 0 27 Sep 2021
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning Ryan Julian Benjamin Swanson Gaurav Sukhatme Sergey Levine Chelsea Finn Karol Hausman OnRL CLL 33 43 0 21 Apr 2020
Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated Priors Rituraj Kaushik Timothée Anne Jean-Baptiste Mouret 32 52 0 10 Mar 2020
Adaptive Prior Selection for Repertoire-based Online Adaptation in Robotics Rituraj Kaushik P. Desreumaux Jean-Baptiste Mouret OffRL 11 34 0 16 Jul 2019
Comparing Semi-Parametric Model Learning Algorithms for Dynamic Model Estimation in Robotics Sebastian Riedel F. Stulp 30 7 0 27 Jun 2019
Proximal Reliability Optimization for Reinforcement Learning Narendra Patwardhan Zequn Wang 18 0 0 03 Jun 2019
Evolving embodied intelligence from materials to machines David Howard A. E. Eiben D. F. Kennedy Jean-Baptiste Mouret P. Valencia Dave Winkler AI4CE 24 107 0 17 Jan 2019
A survey on policy search algorithms for learning robot controllers in a handful of trials Konstantinos Chatzilygeroudis Vassilis Vassiliades F. Stulp Sylvain Calinon Jean-Baptiste Mouret 17 155 0 06 Jul 2018
Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards Rituraj Kaushik Konstantinos Chatzilygeroudis Jean-Baptiste Mouret 31 19 0 25 Jun 2018