Neural Networks To Play Chess

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Neural Networks For Chess

Author : Dominik Klein
Publisher : Independently Published
ISBN 13 :
Total Pages : 268 pages
Book Rating : 4.4/5 (858 download)

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Book Synopsis Neural Networks For Chess by : Dominik Klein

Download or read book Neural Networks For Chess written by Dominik Klein and published by Independently Published. This book was released on 2021-09-28 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Neural Networks have revolutionized computer engines for Go, Shogi and chess. Finally computers are able to evaluate a game position similiar to the way human experts do it. By that, computers are able to identify long-term strategic advantages and disadvantages. But how do chess engines based on neural networks such as AlphaZero, Leela Chess Zero actually work? This book gives an answer to that question. With lots of practical examples and illustrations, all basic building blocks that are required to understand modern chess are introduced. Based on that, the concepts of both classic and modern chess engines are explained. Finally, a miniature version of AlphaZero to play the game Hexapawn is implemented in Python. Chapters include: Single-Layer and Multilayer Perceptrons, Back-Propagation and Gradient Descent, Classification and Regression, Network Vectorization, Convolutional Layers, Squeeze and Excitation Networks, Fully Connected Layers, Batch Normalization, Rectified Linear Unit (ReLU), Residual Layers, Minimax, Alpha-Beta Search, Monte-Carlo Tree Search, AlphaGo, AlphaGo Zero, AlphaZero, Leela Chess Zero (Lc0), Fat Fritz, Effectively Updateable Neural Networks, Fat Fritz 2, Maia, Supervised Learning Hexapawn, Reinforcement Learning of Hexapawn (Hexapawn Zero)

Learn to Play Chess Like a Boss

Author : Patrick Wolff
Publisher : Penguin
ISBN 13 : 1465492232
Total Pages : 758 pages
Book Rating : 4.4/5 (654 download)

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Book Synopsis Learn to Play Chess Like a Boss by : Patrick Wolff

Download or read book Learn to Play Chess Like a Boss written by Patrick Wolff and published by Penguin. This book was released on 2019-09-17 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stop playing like a pawn and start playing like the king You already know just how enjoyable--and and challenging--the game of chess can be. For those who play, chess leads to a lifetime of fun. But how do you make the first move to learn the rules and transform from a pawn to a king? The path to a perfect checkmate is in your hands! In the pages of this book, you'll find an introduction to all the chess pieces including their strengths and weaknesses, tips on how to protect your pieces and prevent their capture, and guidance on when to attack and defend like a boss. You'll also find a bonus tear-out card to take your new tactics on the go!

The AI Revolution in Chess

Author : Joshua Doknjas
Publisher : Everyman Chess
ISBN 13 : 1781945993
Total Pages : 624 pages
Book Rating : 4.7/5 (819 download)

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Book Synopsis The AI Revolution in Chess by : Joshua Doknjas

Download or read book The AI Revolution in Chess written by Joshua Doknjas and published by Everyman Chess. This book was released on with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2018 DeepMind published the shocking results of their chess-playing artificial intelligence software, AlphaZero. Chess players looked in disbelief and immediately wondered how AI would affect the future of chess. Less than a year later, a whole new wave of chess engines emerged that were based on using neural networks to evaluate positions in a completely new way. This book is about the extraordinary impact that AI has had on modern chess. The games of top chess players since the end of 2018 have reflected the use of these new engines in home analysis. They have significantly developed opening theory as well as the general understanding of middlegame concepts. By analysing these games with the help of neural network engines, FIDE Master Joshua Doknjas discusses numerous exciting ideas and examines areas of chess that had previously been overlooked. With thorough explanations, questions, and exercises, this book provides fascinating material for masters and less experienced players alike.

Game Changer

Author : Matthew Sadler
Publisher : New In Chess,Csi
ISBN 13 : 9789056918187
Total Pages : 0 pages
Book Rating : 4.9/5 (181 download)

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Book Synopsis Game Changer by : Matthew Sadler

Download or read book Game Changer written by Matthew Sadler and published by New In Chess,Csi. This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the story behind the self-learning artificial intelligence system with its stunning chess skills

Deep Thinking

Author : Garry Kasparov
Publisher : PublicAffairs
ISBN 13 : 1610397878
Total Pages : 310 pages
Book Rating : 4.6/5 (13 download)

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Book Synopsis Deep Thinking by : Garry Kasparov

Download or read book Deep Thinking written by Garry Kasparov and published by PublicAffairs. This book was released on 2017-05-02 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Garry Kasparov's 1997 chess match against the IBM supercomputer Deep Blue was a watershed moment in the history of technology. It was the dawn of a new era in artificial intelligence: a machine capable of beating the reigning human champion at this most cerebral game. That moment was more than a century in the making, and in this breakthrough book, Kasparov reveals his astonishing side of the story for the first time. He describes how it felt to strategize against an implacable, untiring opponent with the whole world watching, and recounts the history of machine intelligence through the microcosm of chess, considered by generations of scientific pioneers to be a key to unlocking the secrets of human and machine cognition. Kasparov uses his unrivaled experience to look into the future of intelligent machines and sees it bright with possibility. As many critics decry artificial intelligence as a menace, particularly to human jobs, Kasparov shows how humanity can rise to new heights with the help of our most extraordinary creations, rather than fear them. Deep Thinking is a tightly argued case for technological progress, from the man who stood at its precipice with his own career at stake.

The Silicon Road to Chess Improvement

Author : Matthew Sadler
Publisher : New In Chess
ISBN 13 : 9056919849
Total Pages : 982 pages
Book Rating : 4.0/5 (569 download)

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Book Synopsis The Silicon Road to Chess Improvement by : Matthew Sadler

Download or read book The Silicon Road to Chess Improvement written by Matthew Sadler and published by New In Chess. This book was released on 2021-11-13 with total page 982 pages. Available in PDF, EPUB and Kindle. Book excerpt: ‘How can I learn from AlphaZero’s games, aren’t they too advanced for me?’ many club players asked Matthew Sadler after reading his and Natasha Regan’s groundbreaking Game Changer. Here is the answer: you may not be able to replicate their dazzling deep calculations, but every chess player, from club level up, can improve their game by using engines. You will probably be surprised, there is so much more your engine can do for you than just checking and calculating variations! In this thought-provoking new book, based on many years of working with the world’s best chess software, Sadler presents a unique set of methods to work out using your engine. He shows how in your opening preparation, instead of sifting through masses of computer analysis you should play matches against your engine. He also explains how to train your early middlegame play, the conversion of advantages, your positional play, and your defence. And of course: how to analyse your own games. These generic training methods Sadler supplements with concrete middlegame and opening tools. He explains how the top engines tackle crucial middlegame themes such as entrenched pieces, whole board play, ‘attacking rhythm’, exchanging pieces, the march of the Rook’s pawn, queen versus pieces, and many others. He also opens your eyes to typical scenarios that the engines found and fine-tuned in popular openings such as the King’s Indian, the Grünfeld, the Slav, the French and the Sicilian. Sadler illustrates his lessons with a collection of fantastic games, explained with his trademark enthusiasm. For the first time the superhuman powers of the chess engine have been decoded to the benefit of all players, in a rich and highly instructive book.

Deep Learning and the Game of Go

Author : Kevin Ferguson
Publisher : Simon and Schuster
ISBN 13 : 1638354014
Total Pages : 611 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning and the Game of Go by : Kevin Ferguson

Download or read book Deep Learning and the Game of Go written by Kevin Ferguson and published by Simon and Schuster. This book was released on 2019-01-06 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning

Blondie24

Author : David B. Fogel
Publisher : Morgan Kaufmann
ISBN 13 : 9781558607835
Total Pages : 430 pages
Book Rating : 4.6/5 (78 download)

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Book Synopsis Blondie24 by : David B. Fogel

Download or read book Blondie24 written by David B. Fogel and published by Morgan Kaufmann. This book was released on 2002 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how a computer, by replicating the processes of Darwinian evolution, taught itself to play checkers far better than its creators could have programmed it to play. Fogel (editor, IEEE Transactions on Evolutionary Computation) considers the implications for evolutionary computations and artificial intelligence. Diagrams illustrate the evolutionary and computational processes at work, and the course of various games of checkers. Annotation copyrighted by Book News, Inc., Portland, OR.

Artificial Neural Networks and Machine Learning – ICANN 2016

Author : Alessandro E.P. Villa
Publisher : Springer
ISBN 13 : 3319447785
Total Pages : 585 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Artificial Neural Networks and Machine Learning – ICANN 2016 by : Alessandro E.P. Villa

Download or read book Artificial Neural Networks and Machine Learning – ICANN 2016 written by Alessandro E.P. Villa and published by Springer. This book was released on 2016-08-26 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume.

Cognitive Analytics and Reinforcement Learning

Author : Elakkiya R.
Publisher : John Wiley & Sons
ISBN 13 : 1394214030
Total Pages : 388 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Cognitive Analytics and Reinforcement Learning by : Elakkiya R.

Download or read book Cognitive Analytics and Reinforcement Learning written by Elakkiya R. and published by John Wiley & Sons. This book was released on 2024-05-14 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: COGNITIVE ANALYTICS AND REINFORCEMENT LEARNING The combination of cognitive analytics and reinforcement learning is a transformational force in the field of modern technological breakthroughs, reshaping the decision-making, problem-solving, and innovation landscape; this book offers an examination of the profound overlap between these two fields and illuminates its significant consequences for business, academia, and research. Cognitive analytics and reinforcement learning are pivotal branches of artificial intelligence. They have garnered increased attention in the research field and industry domain on how humans perceive, interpret, and respond to information. Cognitive science allows us to understand data, mimic human cognitive processes, and make informed decisions to identify patterns and adapt to dynamic situations. The process enhances the capabilities of various applications. Readers will uncover the latest advancements in AI and machine learning, gaining valuable insights into how these technologies are revolutionizing various industries, including transforming healthcare by enabling smarter diagnosis and treatment decisions, enhancing the efficiency of smart cities through dynamic decision control, optimizing debt collection strategies, predicting optimal moves in complex scenarios like chess, and much more. With a focus on bridging the gap between theory and practice, this book serves as an invaluable resource for researchers and industry professionals seeking to leverage cognitive analytics and reinforcement learning to drive innovation and solve complex problems. The book’s real strength lies in bridging the gap between theoretical knowledge and practical implementation. It offers a rich tapestry of use cases and examples. Whether you are a student looking to gain a deeper understanding of these cutting-edge technologies, an AI practitioner seeking innovative solutions for your projects, or an industry leader interested in the strategic applications of AI, this book offers a treasure trove of insights and knowledge to help you navigate the complex and exciting world of cognitive analytics and reinforcement learning. Audience The book caters to a diverse audience that spans academic researchers, AI practitioners, data scientists, industry leaders, tech enthusiasts, and educators who associate with artificial intelligence, data analytics, and cognitive sciences.

Kaufman's New Repertoire for Black and White

Author : Larry Kaufmann
Publisher : New In Chess,Csi
ISBN 13 : 9789056918620
Total Pages : 0 pages
Book Rating : 4.9/5 (186 download)

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Book Synopsis Kaufman's New Repertoire for Black and White by : Larry Kaufmann

Download or read book Kaufman's New Repertoire for Black and White written by Larry Kaufmann and published by New In Chess,Csi. This book was released on 2019-10-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seven years after his acclaimed and bestselling The Kaufman Repertoire for Black and White, Grandmaster Larry Kaufman is back with his new repertoire book, covering the entire scope of chess openings in one volume. Two important developments made this new book necessary. Larry Kaufman, who routinely himself plays the lines he advocates to others, discovered that after 1.d4 (the recommendation in his previous book) it became nearly impossible to show a consistent advantage for White, especially against the Gruenfeld and the Nimzo/Ragozin defenses. The other factor was that chess engines have become so much stronger in recent years. Komodo, the top chess engine that computer expert Kaufman helped develop, is now able to apply the celebrated Monte Carlo Tree Search algorithm. With Komodo MCTS it is now possible to abandon lines that may be theoretically best against other computers, and instead choose lines that are likely to succeed in actual practice against strong human opponents. Larry Kaufman presents a completely new White repertoire with 1.e4 aiming for an objective advantage in the simplest practical manner. You are presented with two options, while you don't have to play the sharpest lines. The Black repertoire has been thoroughly revised and updated, with some crucial chapters replaced. Kaufman's New Repertoire for Black and White is the first opening book that is primarily based on Monte Carlo search. The highly original analysis has resulted in many improvements on existing theory. This is a ready-to-go and easy-to-digest repertoire with sound, practical lines that do not outdate rapidly and are suitable for masters while accessible for amateurs.

Deep Learning for Coders with fastai and PyTorch

Author : Jeremy Howard
Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Machines that Learn to Play Games

Author : Johannes Fürnkranz
Publisher : Nova Publishers
ISBN 13 : 9781590330210
Total Pages : 318 pages
Book Rating : 4.3/5 (32 download)

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Book Synopsis Machines that Learn to Play Games by : Johannes Fürnkranz

Download or read book Machines that Learn to Play Games written by Johannes Fürnkranz and published by Nova Publishers. This book was released on 2001 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mind-set that has dominated the history of computer game playing relies on straightforward exploitation of the available computing power. The fact that a machine can explore millions of variations sooner than the sluggish human can wink an eye has inspired hopes that the mystery of intelligence can be cracked, or at least side-stepped, by sheer force. Decades of the steadily growing strength of computer programs have attested to the soundness of this approach. It is clear that deeper understanding can cut the amount of necessary calculations by orders of magnitude. The papers collected in this volume describe how to instill learning skills in game playing machines. The reader is asked to keep in mind that this is not just about games -- the possibility that the discussed techniques will be used in control systems and in decision support always looms in the background.

LOGICAL CHESS

Author : Irving Chernev
Publisher : Touchstone
ISBN 13 : 9780671211356
Total Pages : 0 pages
Book Rating : 4.2/5 (113 download)

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Book Synopsis LOGICAL CHESS by : Irving Chernev

Download or read book LOGICAL CHESS written by Irving Chernev and published by Touchstone. This book was released on 1971-06-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: From Simon & Schuster, Logical Chess: Move By Move: Every Move Explained is Irving Chernev guide to beginners chess and the basic moves for every player to improve. In this much loved classic, Irving Chernev explains 33 complete games in detail, telling the reader the reason for every single move. Playing through these games and explanations gives a real insight into the power of the pieces and how to post them most effectively.

Chess Metaphors

Author : Diego Rasskin-Gutman
Publisher : MIT Press
ISBN 13 : 026218267X
Total Pages : 229 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Chess Metaphors by : Diego Rasskin-Gutman

Download or read book Chess Metaphors written by Diego Rasskin-Gutman and published by MIT Press. This book was released on 2009 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: "In Chess Metaphors, Diego Rasskin-Gutman explores fundamental questions about memory, thought, emotion, consciousness, and other cognitive processes through the game of chess, using the moves of thirty-two pieces over sixty-four squares to map the structural and functional organization of the brain." --Book Jacket.

Neural Networks and Deep Learning

Author : Charu C. Aggarwal
Publisher : Springer
ISBN 13 : 3319944630
Total Pages : 512 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Neural Networks and Deep Learning by : Charu C. Aggarwal

Download or read book Neural Networks and Deep Learning written by Charu C. Aggarwal and published by Springer. This book was released on 2018-08-25 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.

Artificial Intelligence with Python

Author : Prateek Joshi
Publisher : Packt Publishing Ltd
ISBN 13 : 1786469677
Total Pages : 437 pages
Book Rating : 4.7/5 (864 download)

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Book Synopsis Artificial Intelligence with Python by : Prateek Joshi

Download or read book Artificial Intelligence with Python written by Prateek Joshi and published by Packt Publishing Ltd. This book was released on 2017-01-27 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.