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You're reading from  Hands-On Intelligent Agents with OpenAI Gym

Product typeBook
Published inJul 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781788836579
Edition1st Edition
Languages
Python
Tools
OpenAI Gym
Concepts
Artificial Intelligence
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Author (1)
Palanisamy P
Palanisamy P
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Palanisamy P

Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.
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Summary

We learned a lot in this chapter. More importantly, we implemented an agent that learned to solve the Mountain Car problem smartly in 7 minutes or so!

We started by understanding the famous Mountain Car problem and looking at how the environment, the observation space, the state space, and rewards are designed in the Gym's MountainCar-v0 environment. We revisited the reinforcement learning Gym boilerplate code we used in the previous chapter and made some improvements to it, which are also available in the code repository of this book.

We then defined the hyperparameters for our Q-learning agent and started implementing a Q-learning algorithm from scratch. We first implemented the agent's initialization function to initialize the agent's internal state variables, including the Q value representation, using a NumPy n-dimensional array. Then, we implemented...

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Hands-On Intelligent Agents with OpenAI Gym
Published in: Jul 2018Publisher: PacktISBN-13: 9781788836579
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Palanisamy P

Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.
Read more about Palanisamy P

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