Curious Explorer: a provable exploration strategy in Policy Learning

29 June 2021

Papers citing "Curious Explorer: a provable exploration strategy in Policy Learning"

11 / 11 papers shown

Title
OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments Jinyi Liu Zhi Wang Yan Zheng Jianye Hao Chenjia Bai Junjie Ye Zhen Wang Haiyin Piao Yang Sun 91 7 0 19 Dec 2023
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 74 101 0 14 Sep 2021
First return, then explore Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune 82 363 0 27 Apr 2020
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning Dipendra Kumar Misra Mikael Henaff A. Krishnamurthy John Langford 79 151 0 13 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 136 108 0 15 Oct 2019
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift Alekh Agarwal Sham Kakade Jason D. Lee G. Mahajan 72 321 0 01 Aug 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 82 194 0 05 Jun 2019
Regret Bounds for Reinforcement Learning via Markov Chain Concentration R. Ortner 69 46 0 06 Aug 2018
Curiosity-driven Exploration by Self-supervised Prediction Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell LRM SSL 122 2,451 0 15 May 2017
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning Christoph Dann Tor Lattimore Emma Brunskill 83 311 0 22 Mar 2017
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 223 5,086 0 05 Jun 2016