[RE] MEDIRL Maximum Entropy Deep Inverse Reinforcement Learning for Human Social Navigation

[nihalgunu]

Original article:
Learning How Pedestrians Navigate: A Deep Inverse Reinforcement Learning Approach
https://par.nsf.gov/servlets/purl/10111828

PDF URL:
https://drive.google.com/file/d/1Ud4husXegrcooQWrjyjaH6UPsevW_7Su/view

Metadata URL:
https://docs.google.com/document/d/1jJngE8_9QGPyu3Q6PxKqrhVrpmbVvS5FblQiwc2DgSs/edit?usp=sharing

Code URL:
https://dagshub.com/ML-Purdue/hackathonf23-Stacks

Scientific domain:
Data-Driven Approach to Human Social Navigation, Human-Robot Interaction within Navigation, Deep Inverse Reinforcement Learning
Programming language:
Python
Suggested editor:

[rougier]

Thanks for your sublmission, we'll assign an editor soon. @koustuvsinha or @gdetor Can you handle this submission?

[vingupta22]

Hey @rougier, I'm the co-author of this paper, is there any update for the review?

[rougier]

@vingupta22 Sorry for delay. No update so far.
@koustuvsinha or @gdetor, can you handle this submission?

[jinensetpal]

Hi @rougier, may I review this submission?

[rougier]

@jinensetpal Sure, thanks for your help.

[rougier]

@ReScience/reviewers We need a second reviewer for Machine Learning / Python article, any takers?

[gdetor]

@rougier I can be the second reviewer.

[rougier]

@gdetor Great, thank !

[rougier]

@jinensetpal @gdetor You can start your review and if you can do it by mid-March that would be great.