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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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Planning with dynamic programming

Dynamic programming is a very general method to efficiently solve problems that can be decomposed into overlapping sub-problems. If you have used any type of recursive function in your code, you might have already got some preliminary flavor of dynamic programming. Dynamic programming, in simple terms, tries to cache or store the results of sub-problems so that they can be used later if required, instead of computing the results again.

Okay, so how is that relevant here, you may ask. Well, they are pretty useful for solving a fully defined MDP, which means that an agent can find the most optimal way to act in an environment to achieve the highest reward using dynamic programming if it has full knowledge of the MDP! In the following table, you will find a concise summary of what the inputs and outputs are when we are interested in sequential prediction...

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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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