Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives

25 June 2019

Papers citing "Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives"

24 / 24 papers shown

Title
Routing Networks and the Challenges of Modular and Compositional Computation Clemens Rosenbaum Ignacio Cases Matthew D Riemer Tim Klinger 64 81 0 29 Apr 2019
Model Primitive Hierarchical Lifelong Reinforcement Learning Bohan Wu Jayesh K. Gupta Mykel J. Kochenderfer OffRL 45 10 0 04 Mar 2019
Neural probabilistic motor primitives for humanoid control J. Merel Leonard Hasenclever Alexandre Galashov Arun Ahuja Vu Pham Greg Wayne Yee Whye Teh N. Heess 78 160 0 28 Nov 2018
Hierarchical visuomotor control of humanoids J. Merel Arun Ahuja Vu Pham S. Tunyasuvunakool Siqi Liu Dhruva Tirumala N. Heess Greg Wayne 92 97 0 23 Nov 2018
Latent Space Policies for Hierarchical Reinforcement Learning Tuomas Haarnoja Kristian Hartikainen Pieter Abbeel Sergey Levine BDL 74 193 0 09 Apr 2018
Diversity is All You Need: Learning Skills without a Reward Function Benjamin Eysenbach Abhishek Gupta Julian Ibarz Sergey Levine 99 1,085 0 16 Feb 2018
Learning Independent Causal Mechanisms Giambattista Parascandolo Niki Kilbertus Mateo Rojas-Carulla Bernhard Schölkopf CML OOD DRL 52 182 0 04 Dec 2017
Meta Learning Shared Hierarchies Kevin Frans Jonathan Ho Xi Chen Pieter Abbeel John Schulman 56 353 0 26 Oct 2017
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation Yuhuai Wu Elman Mansimov Shun Liao Roger C. Grosse Jimmy Ba OffRL 57 629 0 17 Aug 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 499 19,065 0 20 Jul 2017
Emergence of Locomotion Behaviours in Rich Environments N. Heess TB Dhruva S. Sriram Jay Lemmon J. Merel ... Tom Erez Ziyun Wang S. M. Ali Eslami Martin Riedmiller David Silver 202 937 0 07 Jul 2017
Inferring and Executing Programs for Visual Reasoning Justin Johnson B. Hariharan Laurens van der Maaten Judy Hoffman Li Fei-Fei C. L. Zitnick Ross B. Girshick NAI 83 545 0 10 May 2017
Stochastic Neural Networks for Hierarchical Reinforcement Learning Carlos Florensa Yan Duan Pieter Abbeel BDL 90 361 0 10 Apr 2017
FeUdal Networks for Hierarchical Reinforcement Learning A. Vezhnevets Simon Osindero Tom Schaul N. Heess Max Jaderberg David Silver Koray Kavukcuoglu FedML 84 905 0 03 Mar 2017
A Laplacian Framework for Option Discovery in Reinforcement Learning Marlos C. Machado Marc G. Bellemare Michael Bowling 86 263 0 02 Mar 2017
Deep Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon Kevin Patrick Murphy 126 1,721 0 01 Dec 2016
Modular Multitask Reinforcement Learning with Policy Sketches Jacob Andreas Dan Klein Sergey Levine OffRL 145 462 0 06 Nov 2016
The Option-Critic Architecture Pierre-Luc Bacon J. Harb Doina Precup OffRL 64 1,087 0 16 Sep 2016
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 223 5,077 0 05 Jun 2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation Tejas D. Kulkarni Karthik Narasimhan A. Saeedi J. Tenenbaum 71 1,136 0 20 Apr 2016
Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Adria Puigdomenech Badia M. Berk Mirza Alex Graves Timothy Lillicrap Tim Harley David Silver Koray Kavukcuoglu 199 8,859 0 04 Feb 2016
High-Dimensional Continuous Control Using Generalized Advantage Estimation John Schulman Philipp Moritz Sergey Levine Michael I. Jordan Pieter Abbeel OffRL 99 3,414 0 08 Jun 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Kyunghyun Cho B. V. Merrienboer Çağlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio AIMat 1.0K 23,354 0 03 Jun 2014