PyTorch implementation of the Value Iteration Networks (VIN) (NIPS '16 best paper)

Related tags

Deep LearningValue-Iteration-Networks-PyTorch
Overview

Value Iteration Networks in PyTorch

Tamar, A., Wu, Y., Thomas, G., Levine, S., and Abbeel, P. Value Iteration Networks. Neural Information Processing Systems (NIPS) 2016

This repository contains an implementation of Value Iteration Networks (VIN) in PyTorch based on the original Theano implementation by the authors and the TensoFlow implementation by Abhishek Kumar.

VIN won the Best Paper Award at NIPS 2016.

Value Iteration Network and Module

Dependencies

  • Python 2.7
  • PyTorch
  • SciPy >= 0.18.1 (to load the data)

Datasets

Training

python train_main.py

Several arguments can be set in train_main.py like learning rate. Please check train_main.py for details.

python train_main.py --lr 0.001

References

Owner
LEI TAI
Autonomous Driving Solutions
LEI TAI
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