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Fast Exploration with Simplified Models and Approximately Optimistic
  Planning in Model Based Reinforcement Learning

Fast Exploration with Simplified Models and Approximately Optimistic Planning in Model Based Reinforcement Learning

1 June 2018
Ramtin Keramati
Jay Whang
Patrick Cho
Emma Brunskill
    OffRL
ArXivPDFHTML

Papers citing "Fast Exploration with Simplified Models and Approximately Optimistic Planning in Model Based Reinforcement Learning"

3 / 3 papers shown
Title
Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction
Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction
Anthony GX-Chen
Kenneth Marino
Rob Fergus
OCL
63
1
0
21 Aug 2024
Hierarchical reinforcement learning for efficient exploration and
  transfer
Hierarchical reinforcement learning for efficient exploration and transfer
Lorenzo Steccanella
Simone Totaro
Damien Allonsius
Anders Jonsson
BDL
30
8
0
12 Nov 2020
Go-Explore: a New Approach for Hard-Exploration Problems
Go-Explore: a New Approach for Hard-Exploration Problems
Adrien Ecoffet
Joost Huizinga
Joel Lehman
Kenneth O. Stanley
Jeff Clune
AI4TS
24
363
0
30 Jan 2019
1