You're reading from PyTorch 1.x Reinforcement Learning Cookbook

Product typeBook

Published inOct 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781838551964

Edition1st Edition

Languages

Python

Tools

PyTorch

Concepts

Reinforcement Learning

Author (1)

Yuxi (Hayden) Liu

Solving the coin-flipping gamble problem

Gambling on coin flipping should sound familiar to everyone. In each round of the game, the gambler can make a bet on whether a coin flip will show heads. If it turns out heads, the gambler will win the same amount they bet; otherwise, they will lose this amount. The game continues until the gambler loses (ends up with nothing) or wins (wins more than 100 dollars, let's say). Let's say the coin is unfair and it lands on heads 40% of the time. In order to maximize the chance of winning, how much should the gambler bet based on their current capital in each round? This will definitely be an interesting problem to solve.

If the coin lands on heads more than 50% of the time, there is nothing to discuss. The gambler can just keep betting one dollar each round and should win the game most of the time. If it is a fair coin, the gambler...

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PyTorch 1.x Reinforcement Learning Cookbook

Published in: Oct 2019Publisher: PacktISBN-13: 9781838551964

Author (1)

Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.
Read more about Yuxi (Hayden) Liu

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Author (1)

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