Mark Liu - AlphaGo Simplified Rule-Based AI and Deep Learning in Ev

Description: About this Item The item is a book Paperback The Author Name is Mark Liu The Title is AlphaGo Simplified : Rule-Based AI and Deep Learning in Everyday Games Condition New Other Comments Edition Number - 0001. Edition_description - . Pages Count - 408. Binding type - Perfect. Content Language - English Category - COMPUTERS / Artificial Intelligence / General COMPUTERS / Business & Productivity Software / Business Inte COMPUTERS / Programming / Games Product Description - May 11, 1997, was a watershed moment in the history of artificial intelligence (AI): the IBM supercomputer chess engine, Deep Blue, beat the world Chess champion, Garry Kasparov. It was the first time a machine had triumphed over a human player in a Chess tournament. Fast forward 19 years to May 9, 2016, DeepMind’s AlphaGo beat the world Go champion Lee Sedol. AI again stole the spotlight and generated a media frenzy. This time, a new type of AI algorithm, namely machine learning (ML) was the driving force behind the game strategies. What exactly is ML? How is it related to AI? Why is deep learning (DL) so popular these days? This book explains how traditional rule-based AI and ML work and how they can be implemented in everyday games such as Last Coin standing, Tic Tac Toe, or Connect Four. Game rules in these three games are easy to implement. As a result, readers will learn rule-based AI, deep reinforcement learning, and more importantly, how to combine the two to create powerful game strategies (the whole is indeed greater than the sum of its parts) without getting bogged down in complicated game rules. Implementing rule-based AI and ML in these straightforward games is quick and not computationally intensive. Consequently, game strategies can be trained in mere minutes or hours without requiring GPU training or supercomputing facilities, showcasing AI's ability to achieve superhuman performance in these games. More importantly, readers will gain a thorough understanding of the principles behind rule-based AI, such as the MiniMax algorithm, alpha-beta pruning, and Monte Carlo Tree Search (MCTS), and how to integrate them with cutting-edge ML techniques like convolutional neural networks and deep reinforcement learning to apply them in their own business fields and tackle real-world challenges. Written with clarity from the ground up, this book appeals to both general readers and industry professionals who seek to learn about rule-based AI and deep reinforcement learning, as well as students and educators in computer science and programming courses. We Use Stock Images Because we have over 2 million items for sale we have to use stock images, this listing does not include the actual image of the item for sale. The purchase of this specific item is made with the understanding that the image shown in this listing is a stock image and not the actual item for sale. For example: some of our stock images include stickers, labels, price tags, hyper stickers, obi's, promotional messages, signatures and or writing which may not be available in the actual item. When possible we will add details of the items we are selling to help buyers know what is included in the item for sale. The details are provided automatically from our central master database and can sometimes be wrong. Books are released in many editions and variations, such as standard edition, re-issue, not for sale, promotional, special edition, limited edition, and many other editions and versions. The Book you receive could be any of these editions or variations. If you are looking for a specific edition or version please contact us to verify what we are selling. Gift Ideas This is a great Christmas gift idea. Hours of Service We have many warehouses, some of the warehouses process orders seven days a week, but the Administration Support Staff are located at a head office location, outside of the warehouses, and typically work only Monday to Friday. Location ID 9000z iHaveit SKU ID 167437881

Price: 74.91 USD

Location: US

End Time: 2024-12-22T18:02:48.000Z

Shipping Cost: 5.33 USD