Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes

20 October 2023

Papers citing "Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes"

21 / 21 papers shown

Title
Sharing Knowledge in Multi-Task Deep Reinforcement Learning Carlo DÉramo Davide Tateo Andrea Bonarini Marcello Restelli Jan Peters 168 130 0 17 Jan 2024
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations Ruiquan Huang Yitao Liang J. Yang OffRL 55 5 0 01 Jul 2023
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms Fan Chen Yu Bai Song Mei 66 22 0 29 Sep 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 52 39 0 12 Jul 2022
Joint Representation Training in Sequential Tasks with Shared Structure Aldo Pacchiano Ofir Nachum Nilseh Tripuraneni Peter L. Bartlett 95 5 0 24 Jun 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 79 36 0 24 Jun 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 73 23 0 15 Jun 2022
Provable General Function Class Representation Learning in Multitask Bandits and MDPs Rui Lu Andrew Zhao S. Du Gao Huang OffRL 99 10 0 31 May 2022
Provable Benefits of Representational Transfer in Reinforcement Learning Alekh Agarwal Yuda Song Wen Sun Kaiwen Wang Mengdi Wang Xuezhou Zhang OffRL 91 35 0 29 May 2022
The Statistical Complexity of Interactive Decision Making Dylan J. Foster Sham Kakade Jian Qian Alexander Rakhlin 370 180 0 27 Dec 2021
Provably Efficient Multi-Task Reinforcement Learning with Model Transfer Chicheng Zhang Zhi Wang OffRL 59 19 0 19 Jul 2021
On the Power of Multitask Representation Learning in Linear MDP Rui Lu Gao Huang S. Du 53 29 0 15 Jun 2021
Near-optimal Representation Learning for Linear Bandits and Linear RL Jiachen Hu Xiaoyu Chen Chi Jin Lihong Li Liwei Wang OffRL 153 53 0 08 Feb 2021
CURL: Contrastive Unsupervised Representations for Reinforcement Learning A. Srinivas Michael Laskin Pieter Abbeel SSL DRL OffRL 83 1,087 0 08 Apr 2020
Learning Near Optimal Policies with Low Inherent Bellman Error Andrea Zanette A. Lazaric Mykel Kochenderfer Emma Brunskill OffRL 71 222 0 29 Feb 2020
Provable Representation Learning for Imitation Learning via Bi-level Optimization Sanjeev Arora S. Du Sham Kakade Yuping Luo Nikunj Saunshi 62 61 0 24 Feb 2020
Representation Learning with Contrastive Predictive Coding Aaron van den Oord Yazhe Li Oriol Vinyals DRL SSL 318 10,284 0 10 Jul 2018
Curiosity-driven Exploration by Self-supervised Prediction Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell LRM SSL 106 2,437 0 15 May 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 89 772 0 15 Nov 2016
Sample Complexity of Multi-task Reinforcement Learning Emma Brunskill Lihong Li 81 138 0 26 Sep 2013
Closing the Learning-Planning Loop with Predictive State Representations Byron Boots S. Siddiqi Geoffrey J. Gordon 236 265 0 12 Dec 2009