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You're reading from  TensorFlow Reinforcement Learning Quick Start Guide

Product typeBook
Published inMar 2019
PublisherPackt
ISBN-139781789533583
Edition1st Edition
Tools
TensorFlow
Concepts
Reinforcement Learning
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Author (1)
Kaushik Balakrishnan
Kaushik Balakrishnan
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Kaushik Balakrishnan

Kaushik Balakrishnan works for BMW in Silicon Valley, and applies reinforcement learning, machine learning, and computer vision to solve problems in autonomous driving. Previously, he also worked at Ford Motor Company and NASA Jet Propulsion Laboratory. His primary expertise is in machine learning, computer vision, and high-performance computing, and he has worked on several projects involving both research and industrial applications. He has also worked on numerical simulations of rocket landings on planetary surfaces, and for this he developed several high-fidelity models that run efficiently on supercomputers. He holds a PhD in aerospace engineering from the Georgia Institute of Technology in Atlanta, Georgia.
Read more about Kaushik Balakrishnan

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Learning to use TORCS

We will first learn how to use the TORCS racing car simulator, which is an open source simulator. You can obtain the download instructions from http://torcs.sourceforge.net/index.php?name=Sections&op=viewarticle&artid=3 but the salient steps are summarized as follows for Linux:

  1. Download the torcs-1.3.7.tar.bz2 file from https://sourceforge.net/projects/torcs/files/all-in-one/1.3.7/torcs-1.3.7.tar.bz2/download
  2. Unpack the package with tar xfvj torcs-1.3.7.tar.bz2
  3. Run the following commands:
    • cd torcs-1.3.7
    • ./configure
    • make
    • make install
    • make datainstall

  4. The default installation directories are:

    • /usr/local/bin: TORCS command (directory should be in your PATH)
    • /usr/local/lib/torcs: TORCS dynamic libs (directory MUST be in your LD_LIBRARY_PATH if you don't use the TORCS shell)
    • /usr/local/share/games/torcs: TORCS data files

By running the torcs...

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TensorFlow Reinforcement Learning Quick Start Guide
Published in: Mar 2019Publisher: PacktISBN-13: 9781789533583
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Kaushik Balakrishnan

Kaushik Balakrishnan works for BMW in Silicon Valley, and applies reinforcement learning, machine learning, and computer vision to solve problems in autonomous driving. Previously, he also worked at Ford Motor Company and NASA Jet Propulsion Laboratory. His primary expertise is in machine learning, computer vision, and high-performance computing, and he has worked on several projects involving both research and industrial applications. He has also worked on numerical simulations of rocket landings on planetary surfaces, and for this he developed several high-fidelity models that run efficiently on supercomputers. He holds a PhD in aerospace engineering from the Georgia Institute of Technology in Atlanta, Georgia.
Read more about Kaushik Balakrishnan

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