Provably efficient RL with Rich Observations via Latent State Decoding

Provably efficient RL with Rich Observations via Latent State Decoding

25 January 2019

A. Krishnamurthy

Miroslav Dudík

Papers citing "Provably efficient RL with Rich Observations via Latent State Decoding"

14 / 14 papers shown

Title
On Generalization Across Environments In Multi-Objective Reinforcement Learning Jayden Teoh Pradeep Varakantham Peter Vamplew OffRL 55 1 0 02 Mar 2025
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory Alexander Levine Peter Stone Amy Zhang OffRL 53 0 0 03 Oct 2024
Invariant Causal Prediction for Block MDPs Amy Zhang Clare Lyle Shagun Sodhani Angelos Filos Marta Z. Kwiatkowska Joelle Pineau Y. Gal Doina Precup OffRL AI4CE OOD 64 139 0 12 Mar 2020
Is Q-learning Provably Efficient? Chi Jin Zeyuan Allen-Zhu Sébastien Bubeck Michael I. Jordan OffRL 44 801 0 10 Jul 2018
Value Prediction Network Junhyuk Oh Satinder Singh Honglak Lee 62 332 0 11 Jul 2017
Curiosity-driven Exploration by Self-supervised Prediction Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell LRM SSL 93 2,416 0 15 May 2017
Count-Based Exploration with Neural Density Models Georg Ostrovski Marc G. Bellemare Aaron van den Oord Rémi Munos 67 616 0 03 Mar 2017
The Predictron: End-To-End Learning and Planning David Silver H. V. Hasselt Matteo Hessel Tom Schaul A. Guez ... Gabriel Dulac-Arnold David P. Reichert Neil C. Rabinowitz André Barreto T. Degris 40 289 0 28 Dec 2016
Reinforcement Learning in Rich-Observation MDPs using Spectral Methods Kamyar Azizzadenesheli A. Lazaric Anima Anandkumar 39 30 0 11 Nov 2016
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable Nan Jiang A. Krishnamurthy Alekh Agarwal John Langford Robert Schapire 71 417 0 29 Oct 2016
Reinforcement Learning of POMDPs using Spectral Methods Kamyar Azizzadenesheli A. Lazaric Anima Anandkumar 22 127 0 25 Feb 2016
Deep Exploration via Bootstrapped DQN Ian Osband Charles Blundell Alexander Pritzel Benjamin Van Roy 53 1,302 0 15 Feb 2016
Selecting Near-Optimal Approximate State Representations in Reinforcement Learning R. Ortner Odalric-Ambrym Maillard D. Ryabko 109 27 0 12 May 2014
PAC Bounds for Discounted MDPs Tor Lattimore Marcus Hutter 57 188 0 17 Feb 2012