Skip to Content
Python Deep Learning - Second Edition
book

Python Deep Learning - Second Edition

by Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
January 2019
Intermediate to advanced
386 pages
11h 13m
English
Packt Publishing
Content preview from Python Deep Learning - Second Edition

Imitiation driving policy

In the section Components of an AV system we outlined several modules, necessary for a self-driving system. In this section we'll discuss how to implement one of them - the driving policy - with the help of DL. One way to do this is with RL, where the car is the agent and the environment is, well, the environment. Another popular approach is imitation learning, where the model (network) learns to imitate the actions of an expert (human). Let's see the properties of imitation learning in the AV scenario:

  • We'll use a type of imitation learning, known as behavioral cloning. This simply means that we'll train our network in a supervised way. Alternatively, we have imitation learning in RL scenario, which is known as ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Python Deep Learning

Python Deep Learning

Valentino Zocca, Gianmario Spacagna, Daniel Slater, Peter Roelants

Publisher Resources

ISBN: 9781789348460Supplemental Content