Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning

6 March 2018

Papers citing "Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning"

6 / 6 papers shown

Title
Low Emission Building Control with Zero-Shot Reinforcement Learning Scott Jeen Alessandro Abate Jonathan M. Cullen AI4CE 17 5 0 28 Jun 2022
Video2Skill: Adapting Events in Demonstration Videos to Skills in an Environment using Cyclic MDP Homomorphisms S. Sontakke Sumegh Roychowdhury Mausoom Sarkar Nikaash Puri Balaji Krishnamurthy Laurent Itti 24 1 0 08 Sep 2021
Mastering Atari with Discrete World Models Danijar Hafner Timothy Lillicrap Mohammad Norouzi Jimmy Ba DRL 19 809 0 05 Oct 2020
Trade-off on Sim2Real Learning: Real-world Learning Faster than Simulations Jingyi Huang Yizheng Zhang F. Giardina A. Rosendo OffRL 14 1 0 21 Jul 2020
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 17 154 0 06 Jul 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 261 9,136 0 06 Jun 2015