You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

Product typeBook

Published inJan 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781838826994

Edition2nd Edition

Languages

Python

Tools

Keras TensorFlow

Concepts

Deep Reinforcement Learning

Author (1)

Maxim Lapan

The Rubik's Cube and combinatorial optimization

I doubt it's possible to find a person who hasn't heard about the Rubik's Cube, so I'm not going to repeat the Wikipedia description (https://en.wikipedia.org/wiki/Rubik%27s_Cube) of this puzzle, but rather focus on the connections it has to mathematics and computer science. If it's not explicitly stated, by "cube" I mean the 3×3 classic Rubik's Cube. There are lots of variations based on the original 3×3 puzzle, but they are still far less popular than the classic invention.

Despite being quite simple in terms of mechanics and the task at hand, the cube is quite a tricky object in terms of all the transformations we can make by possible rotations of its sides. It was calculated that in total, the cube has ~4.33 × 10¹⁹ distinct states reachable by rotating it. That's only the states that are reachable without disassembling the cube; by taking it apart and then assembling...

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Deep Reinforcement Learning Hands-On. - Second Edition

Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994

Author (1)

Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

The Rubik's Cube and combinatorial optimization

Unlock this book and the full library FREE for 7 days

Author (1)

TensorFlow Reinforcement Learning Quick Start Guide

Deep Reinforcement Learning with Python

Hands-On Intelligent Agents with OpenAI Gym

Hands-On Q-Learning with Python

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