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Identify, Estimate and Bound the Uncertainty of Reinforcement Learning
  for Autonomous Driving

Identify, Estimate and Bound the Uncertainty of Reinforcement Learning for Autonomous Driving

12 May 2023
Weitao Zhou
Zhong Cao
Nanshan Deng
Kun Jiang
Diange Yang
    OffRL
ArXivPDFHTML

Papers citing "Identify, Estimate and Bound the Uncertainty of Reinforcement Learning for Autonomous Driving"

5 / 5 papers shown
Title
Efficient and Generalized end-to-end Autonomous Driving System with
  Latent Deep Reinforcement Learning and Demonstrations
Efficient and Generalized end-to-end Autonomous Driving System with Latent Deep Reinforcement Learning and Demonstrations
Zuojin Tang
Xiaoyu Chen
YongQiang Li
Jianyu Chen
24
2
0
22 Jan 2024
Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications
Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications
Jun Wang
Hosein Hasanbeig
Kaiyuan Tan
Zihe Sun
Y. Kantaros
29
3
0
28 Nov 2023
COMBO: Conservative Offline Model-Based Policy Optimization
COMBO: Conservative Offline Model-Based Policy Optimization
Tianhe Yu
Aviral Kumar
Rafael Rafailov
Aravind Rajeswaran
Sergey Levine
Chelsea Finn
OffRL
219
413
0
16 Feb 2021
Autonomous Vehicles that Interact with Pedestrians: A Survey of Theory
  and Practice
Autonomous Vehicles that Interact with Pedestrians: A Survey of Theory and Practice
Amir Rasouli
John K. Tsotsos
51
606
0
30 May 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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