A Distributional Perspective on Reinforcement Learning

21 July 2017

Papers citing "A Distributional Perspective on Reinforcement Learning"

24 / 274 papers shown

Title
Temporal Difference Variational Auto-Encoder Karol Gregor George Papamakarios F. Besse Lars Buesing Theophane Weber DRL 24 126 0 08 Jun 2018
Equivalence Between Wasserstein and Value-Aware Loss for Model-based Reinforcement Learning Kavosh Asadi Evan Cater Dipendra Kumar Misra Michael L. Littman OffRL 21 11 0 01 Jun 2018
Playing hard exploration games by watching YouTube Y. Aytar Tobias Pfaff David Budden T. Paine Ziyun Wang Nando de Freitas 35 269 0 29 May 2018
Meta-Gradient Reinforcement Learning Zhongwen Xu H. V. Hasselt David Silver 53 324 0 24 May 2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning Joshua Romoff Peter Henderson Alexandre Piché Vincent François-Lavet Joelle Pineau 6 42 0 09 May 2018
Exploration by Distributional Reinforcement Learning Yunhao Tang Shipra Agrawal OOD 41 30 0 04 May 2018
Lipschitz Continuity in Model-based Reinforcement Learning Kavosh Asadi Dipendra Kumar Misra Michael L. Littman KELM 43 150 0 19 Apr 2018
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid Mikayel Samvelyan Christian Schroeder de Witt Gregory Farquhar Jakob N. Foerster Shimon Whiteson 84 1,656 0 30 Mar 2018
Policy Search in Continuous Action Domains: an Overview Olivier Sigaud F. Stulp 16 72 0 13 Mar 2018
Accelerated Methods for Deep Reinforcement Learning Adam Stooke Pieter Abbeel OffRL OnRL 25 133 0 07 Mar 2018
Distributed Prioritized Experience Replay Dan Horgan John Quan David Budden Gabriel Barth-Maron Matteo Hessel H. V. Hasselt David Silver 89 731 0 02 Mar 2018
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research Matthias Plappert Marcin Andrychowicz Alex Ray Bob McGrew Bowen Baker ... Joshua Tobin Maciek Chociej Peter Welinder Vikash Kumar Wojciech Zaremba 33 557 0 26 Feb 2018
Temporal Difference Models: Model-Free Deep RL for Model-Based Control Vitchyr H. Pong S. Gu Murtaza Dalal Sergey Levine OffRL 66 238 0 25 Feb 2018
DeepMind Control Suite Yuval Tassa Yotam Doron Alistair Muldal Tom Erez Yazhe Li ... A. Abdolmaleki J. Merel Andrew Lefrancq Timothy Lillicrap Martin Riedmiller ELM LM&Ro BDL 47 1,099 0 02 Jan 2018
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning F. Such Vashisht Madhavan Edoardo Conti Joel Lehman Kenneth O. Stanley Jeff Clune 47 686 0 18 Dec 2017
AI Safety Gridworlds Jan Leike Miljan Martic Victoria Krakovna Pedro A. Ortega Tom Everitt Andrew Lefrancq Laurent Orseau Shane Legg 23 250 0 27 Nov 2017
Distributional Reinforcement Learning with Quantile Regression Will Dabney Mark Rowland Marc G. Bellemare Rémi Munos 21 749 0 27 Oct 2017
Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation G. Kahn Adam R. Villaflor Bosen Ding Pieter Abbeel Sergey Levine SSL 31 287 0 29 Sep 2017
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents Marlos C. Machado Marc G. Bellemare Erik Talvitie J. Veness Matthew J. Hausknecht Michael Bowling 35 544 0 18 Sep 2017
The Uncertainty Bellman Equation and Exploration Brendan O'Donoghue Ian Osband Rémi Munos Volodymyr Mnih 27 186 0 15 Sep 2017
A Brief Survey of Deep Reinforcement Learning Kai Arulkumaran M. Deisenroth Miles Brundage Anil Anthony Bharath OffRL 62 2,776 0 19 Aug 2017
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 41 300 0 22 Mar 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 104 1,503 0 25 Jan 2017
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 272 2,553 0 25 Jan 2016