PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

4 February 2019

Jan Peters

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Papers citing "PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos"

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Title
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 578 2,047 0 04 May 2020
Dream to Control: Learning Behaviors by Latent Imagination Danijar Hafner Timothy Lillicrap Jimmy Ba Mohammad Norouzi VLM 167 1,376 0 03 Dec 2019
A unified view of likelihood ratio and reparameterization gradients and an optimal importance sampling scheme Paavo Parmas Masashi Sugiyama 48 3 0 14 Oct 2019
Regularizing Model-Based Planning with Energy-Based Models Rinu Boney Arno Solin Alexander Ilin 76 18 0 12 Oct 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 91 415 0 25 Jun 2019
Regularizing Trajectory Optimization with Denoising Autoencoders Rinu Boney Norman Di Palo Mathias Berglund Alexander Ilin Arno Solin Antti Rasmus Harri Valpola 56 10 0 28 Mar 2019
Total stochastic gradient algorithms and applications in reinforcement learning Paavo Parmas 72 17 0 05 Feb 2019
Understanding and correcting pathologies in the training of learned optimizers Luke Metz Niru Maheswaranathan Jeremy Nixon C. Freeman Jascha Narain Sohl-Dickstein ODL 101 148 0 24 Oct 2018
Variance reduction properties of the reparameterization trick Ming Xu M. Quiroz Robert Kohn Scott A. Sisson AAML 103 69 0 27 Sep 2018
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 103 155 0 06 Jul 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models Kurtland Chua Roberto Calandra R. McAllister Sergey Levine BDL 232 1,286 0 30 May 2018