RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem

25 November 2020

Papers citing "RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem"

6 / 6 papers shown

Title
Acme: A Research Framework for Distributed Reinforcement Learning Matthew W. Hoffman Bobak Shahriari John Aslanides Gabriel Barth-Maron Nikola Momchev ... Srivatsan Srinivasan A. Cowie Ziyun Wang Bilal Piot Nando de Freitas 90 225 0 01 Jun 2020
Model-Based Reinforcement Learning via Meta-Policy Optimization I. Clavera Jonas Rothfuss John Schulman Yasuhiro Fujita Tamim Asfour Pieter Abbeel 59 225 0 14 Sep 2018
Distributed Prioritized Experience Replay Dan Horgan John Quan David Budden Gabriel Barth-Maron Matteo Hessel H. V. Hasselt David Silver 126 736 0 02 Mar 2018
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures L. Espeholt Hubert Soyer Rémi Munos Karen Simonyan Volodymyr Mnih ... Vlad Firoiu Tim Harley Iain Dunning Shane Legg Koray Kavukcuoglu 129 1,584 0 05 Feb 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 737 11,793 0 09 Mar 2017
Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Adria Puigdomenech Badia M. Berk Mirza Alex Graves Timothy Lillicrap Tim Harley David Silver Koray Kavukcuoglu 150 8,805 0 04 Feb 2016