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RE-MOVE: An Adaptive Policy Design for Robotic Navigation Tasks in Dynamic Environments via Language-Based Feedback

RE-MOVE: An Adaptive Policy Design for Robotic Navigation Tasks in Dynamic Environments via Language-Based Feedback

Souradip Chakraborty
K. Weerakoon
Prithvi Poddar
Mohamed Bashir Elnoor
Priya Narayanan
Carl E. Busart
Pratap Tokekar
Amrit Singh Bedi
Tianyi Zhou
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Papers citing "RE-MOVE: An Adaptive Policy Design for Robotic Navigation Tasks in Dynamic Environments via Language-Based Feedback"

3 / 3 papers shown
Title
Challenges of Real-World Reinforcement Learning
Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold
D. Mankowitz
Todd Hester
OffRL
57
545
0
29 Apr 2019
Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables
Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables
Stefan Depeweg
José Miguel Hernández-Lobato
Finale Doshi-Velez
Steffen Udluft
PER
UQCV
UD
BDL
36
43
0
26 Jun 2017
A Joint Model of Language and Perception for Grounded Attribute Learning
A Joint Model of Language and Perception for Grounded Attribute Learning
Cynthia Matuszek
Nicholas FitzGerald
Luke Zettlemoyer
Liefeng Bo
Dieter Fox
LM&Ro
46
316
0
27 Jun 2012

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