Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning

13 November 2019

Papers citing "Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning"

6 / 56 papers shown

Title
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs Alekh Agarwal Sham Kakade A. Krishnamurthy Wen Sun OffRL 41 223 0 18 Jun 2020
$Q$ -learning with Logarithmic Regret Kunhe Yang Lin F. Yang S. Du 43 59 0 16 Jun 2020
Preference-based Reinforcement Learning with Finite-Time Guarantees Yichong Xu Ruosong Wang Lin F. Yang Aarti Singh A. Dubrawski 33 53 0 16 Jun 2020
Deep Reinforcement and InfoMax Learning Bogdan Mazoure Rémi Tachet des Combes T. Doan Philip Bachman R. Devon Hjelm AI4CE 25 108 0 12 Jun 2020
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization Jianhao Wang Zhizhou Ren Beining Han Jianing Ye Chongjie Zhang OffRL 31 32 0 31 May 2020
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020