 Imitation-Learning-Dagger-Torcs
 Imitation-Learning-Dagger-Torcs 
 Imitation learning example
 This repository provides an example of implementing Imitation Learning with Dataset Aggregation (DAGGER) on the Torcs environment using Python.
A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env
71 stars
 4 watching
 28 forks
 
Language: Python 
last commit: about 8 years ago 
Linked from   1 awesome list  
  daggergym-torcsimitation-learningtensorflowtensorflow-tutorialstensorlayertorcstorcs-env 
 Related projects:
| Repository | Description | Stars | 
|---|---|---|
|  | Provides clean implementations of imitation and reward learning algorithms | 1,350 | 
|  | A system for approximating word embeddings using character-level neural networks | 153 | 
|  | Implementation of a conditional imitation learning policy in PyTorch for autonomous driving using the Carla dataset. | 65 | 
|  | A hands-on introduction to deep learning using PyTorch, explaining mathematical concepts through code examples | 331 | 
|  | A framework for training and testing imitation learning models in the CARLA simulator. | 235 | 
|  | A collection of implementations of recent deep learning papers in Python | 1,814 | 
|  | Project implementing a method to improve deep learning model robustness by re-weighting examples with noisy labels | 269 | 
|  | Code for training universal paraphrastic sentence embeddings and models on semantic similarity tasks | 193 | 
|  | A PyTorch implementation of the skip-gram model for learning word embeddings. | 188 | 
|  | A collection of examples and code snippets teaching machine learning concepts to security professionals through hands-on Python projects | 151 | 
|  | An implementation of the Learning to Compare paper in PyTorch | 251 | 
|  | A collection of tutorials and resources on implementing deep learning models using Python libraries such as Keras and Lasagne. | 426 | 
|  | A collection of tutorials and lessons on building deep learning models using the PyTorch library. | 326 | 
|  | A tutorial on applying machine learning to practical situations using the scikit-learn library | 130 | 
|  | An implementation of semantic image synthesis via adversarial learning using PyTorch | 145 |