Generalization and Exploration via Randomized Value Functions

4 February 2014

Papers citing "Generalization and Exploration via Randomized Value Functions"

46 / 96 papers shown

Title
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play Qinghua Liu Tiancheng Yu Yu Bai Chi Jin 41 121 0 04 Oct 2020
Is Q-Learning Provably Efficient? An Extended Analysis Kushagra Rastogi Jonathan Lee Fabrice Harel-Canada Aditya Sunil Joglekar OffRL 19 1 0 22 Sep 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 41 64 0 18 Aug 2020
Single-partition adaptive Q-learning J. Araújo Mário A. T. Figueiredo M. Botto OffRL 25 2 0 14 Jul 2020
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning Kimin Lee Michael Laskin A. Srinivas Pieter Abbeel OffRL 30 201 0 09 Jul 2020
Near-Optimal Reinforcement Learning with Self-Play Yunru Bai Chi Jin Tiancheng Yu 29 130 0 22 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 38 83 0 15 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 62 300 0 01 Jun 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie Yudong Chen Zhaoran Wang Zhuoran Yang 46 125 0 17 Feb 2020
Provable Self-Play Algorithms for Competitive Reinforcement Learning Yu Bai Chi Jin SSL 32 149 0 10 Feb 2020
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills Victor Campos Alexander R. Trott Caiming Xiong R. Socher Xavier Giró-i-Nieto Jordi Torres OffRL 19 151 0 10 Feb 2020
Adaptive Approximate Policy Iteration Botao Hao N. Lazić Yasin Abbasi-Yadkori Pooria Joulani Csaba Szepesvári 18 14 0 08 Feb 2020
Making Sense of Reinforcement Learning and Probabilistic Inference Brendan O'Donoghue Ian Osband Catalin Ionescu OffRL 37 48 0 03 Jan 2020
Scaling active inference Alexander Tschantz Manuel Baltieri A. Seth Christopher L. Buckley BDL AI4CE 24 68 0 24 Nov 2019
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes Chen-Yu Wei Mehdi Jafarnia-Jahromi Haipeng Luo Hiteshi Sharma R. Jain 109 104 0 15 Oct 2019
Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? Ofir Nachum Haoran Tang Xingyu Lu S. Gu Honglak Lee Sergey Levine 29 100 0 23 Sep 2019
Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin Zhuoran Yang Zhaoran Wang Michael I. Jordan 57 546 0 11 Jul 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 32 8 0 10 Jun 2019
Estimating Risk and Uncertainty in Deep Reinforcement Learning W. Clements B. V. Delft Benoît-Marie Robaglia Reda Bahi Slaoui Sébastien Toth 40 96 0 23 May 2019
A Bayesian Approach to Robust Reinforcement Learning E. Derman D. Mankowitz Timothy A. Mann Shie Mannor 28 58 0 20 May 2019
Context-Dependent Upper-Confidence Bounds for Directed Exploration Raksha Kumaraswamy M. Schlegel Adam White Martha White OffRL 31 12 0 15 Nov 2018
Policy Certificates: Towards Accountable Reinforcement Learning Christoph Dann Ashutosh Adhikari Wei Wei Jimmy J. Lin OffRL 30 141 0 07 Nov 2018
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning David Janz Jiri Hron Przemysław Mazur Katja Hofmann José Miguel Hernández-Lobato Sebastian Tschiatschek 65 51 0 15 Oct 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 32 373 0 08 Jun 2018
The Uncertainty Bellman Equation and Exploration Brendan O'Donoghue Ian Osband Rémi Munos Volodymyr Mnih 41 189 0 15 Sep 2017
Reverse Curriculum Generation for Reinforcement Learning Carlos Florensa David Held Markus Wulfmeier Michael Zhang Pieter Abbeel 36 438 0 17 Jul 2017
Noisy Networks for Exploration Meire Fortunato M. G. Azar Bilal Piot Jacob Menick Ian Osband ... Rémi Munos Demis Hassabis Olivier Pietquin Charles Blundell Shane Legg 30 889 0 30 Jun 2017
Count-Based Exploration in Feature Space for Reinforcement Learning Jarryd Martin S. N. Sasikumar Tom Everitt Marcus Hutter 24 122 0 25 Jun 2017
On Optimistic versus Randomized Exploration in Reinforcement Learning Ian Osband Benjamin Van Roy 26 10 0 13 Jun 2017
Parameter Space Noise for Exploration Matthias Plappert Rein Houthooft Prafulla Dhariwal Szymon Sidor Richard Y. Chen Xi Chen Tamim Asfour Pieter Abbeel Marcin Andrychowicz 31 593 0 06 Jun 2017
From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood Kelvin Guu Panupong Pasupat Emmy Liu Percy Liang 34 190 0 25 Apr 2017
Stochastic Neural Networks for Hierarchical Reinforcement Learning Carlos Florensa Yan Duan Pieter Abbeel BDL 47 360 0 10 Apr 2017
Thompson Sampling for Linear-Quadratic Control Problems Marc Abeille A. Lazaric 25 55 0 27 Mar 2017
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 53 300 0 22 Mar 2017
Count-Based Exploration with Neural Density Models Georg Ostrovski Marc G. Bellemare Aaron van den Oord Rémi Munos 50 616 0 03 Mar 2017
A Laplacian Framework for Option Discovery in Reinforcement Learning Marlos C. Machado Marc G. Bellemare Michael Bowling 31 261 0 02 Mar 2017
Gaussian-Dirichlet Posterior Dominance in Sequential Learning Ian Osband Benjamin Van Roy 27 8 0 14 Feb 2017
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning Haoran Tang Rein Houthooft Davis Foote Adam Stooke Xi Chen Yan Duan John Schulman F. Turck Pieter Abbeel OffRL 60 762 0 15 Nov 2016
Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks Nicolas Usunier Gabriel Synnaeve Zeming Lin Soumith Chintala 30 138 0 10 Sep 2016
Why is Posterior Sampling Better than Optimism for Reinforcement Learning? Ian Osband Benjamin Van Roy BDL 29 255 0 01 Jul 2016
VIME: Variational Information Maximizing Exploration Rein Houthooft Xi Chen Yan Duan John Schulman F. Turck Pieter Abbeel 27 78 0 31 May 2016
Angrier Birds: Bayesian reinforcement learning Imanol Arrieta-Ibarra Bernardo Ramos Lars Roemheld 12 1 0 06 Jan 2016
Efficient Learning in Large-Scale Combinatorial Semi-Bandits Zheng Wen Branislav Kveton Azin Ashkan OffRL 59 96 0 28 Jun 2014
Near-optimal Reinforcement Learning in Factored MDPs Ian Osband Benjamin Van Roy 47 120 0 15 Mar 2014
Optimal Demand Response Using Device Based Reinforcement Learning Zheng Wen D. OÑeill H. Maei OffRL 32 232 0 08 Jan 2014
Efficient Reinforcement Learning in Deterministic Systems with Value Function Generalization Zheng Wen Benjamin Van Roy 31 42 0 18 Jul 2013