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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.
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Using PPO to solve the MountainCar problem

We will solve the MountainCar problem using PPO. MountainCar involves a car trapped in the valley of a mountain. It has to apply throttle to accelerate against gravity and try to drive out of the valley up steep mountain walls to reach a desired flag point on the top of the mountain. You can see a schematic of the MountainCar problem from OpenAI Gym at https://gym.openai.com/envs/MountainCar-v0/.

This problem is very challenging, as the agent cannot just apply full throttle from the base of the mountain and try to reach the flag point, as the mountain walls are steep and gravity will not allow the car to achieve sufficient enough momentum. The optimal solution is for the car to initially go backward and then step on the throttle to pick up enough momentum to overcome gravity and successfully drive out of the valley. We will see that the...

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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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