Machines That Learn To Play Games

Machines That Learn To Play Games Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Machines That Learn To Play Games book. This book definitely worth reading, it is an incredibly well-written.

Machines that Learn to Play Games

Johannes Fürnkranz,Miroslav Kubat
Machines that Learn to Play Games Book PDF

Author : Johannes Fürnkranz,Miroslav Kubat
Publisher : Nova Publishers
Page : 318 pages
File Size : 45,6 Mb
Release : 2001
Category : Computers
ISBN : 1590330218

Get Book

Machines that Learn to Play Games by Johannes Fürnkranz,Miroslav Kubat Pdf

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.

Preference Learning

Johannes Fürnkranz,Eyke Hüllermeier
Preference Learning Book PDF

Author : Johannes Fürnkranz,Eyke Hüllermeier
Publisher : Springer Science & Business Media
Page : 457 pages
File Size : 47,7 Mb
Release : 2010-11-19
Category : Computers
ISBN : 9783642141256

Get Book

Preference Learning by Johannes Fürnkranz,Eyke Hüllermeier Pdf

The topic of preferences is a new branch of machine learning and data mining, and it has attracted considerable attention in artificial intelligence research in previous years. It involves learning from observations that reveal information about the preferences of an individual or a class of individuals. Representing and processing knowledge in terms of preferences is appealing as it allows one to specify desires in a declarative way, to combine qualitative and quantitative modes of reasoning, and to deal with inconsistencies and exceptions in a flexible manner. And, generalizing beyond training data, models thus learned may be used for preference prediction. This is the first book dedicated to this topic, and the treatment is comprehensive. The editors first offer a thorough introduction, including a systematic categorization according to learning task and learning technique, along with a unified notation. The first half of the book is organized into parts on label ranking, instance ranking, and object ranking; while the second half is organized into parts on applications of preference learning in multiattribute domains, information retrieval, and recommender systems. The book will be of interest to researchers and practitioners in artificial intelligence, in particular machine learning and data mining, and in fields such as multicriteria decision-making and operations research.

Playing Smart

Julian Togelius
Playing Smart Book PDF

Author : Julian Togelius
Publisher : MIT Press
Page : 188 pages
File Size : 43,8 Mb
Release : 2019-01-15
Category : Games & Activities
ISBN : 9780262039031

Get Book

Playing Smart by Julian Togelius Pdf

A new vision of the future of games and game design, enabled by AI. Can games measure intelligence? How will artificial intelligence inform games of the future? In Playing Smart, Julian Togelius explores the connections between games and intelligence to offer a new vision of future games and game design. Video games already depend on AI. We use games to test AI algorithms, challenge our thinking, and better understand both natural and artificial intelligence. In the future, Togelius argues, game designers will be able to create smarter games that make us smarter in turn, applying advanced AI to help design games. In this book, he tells us how. Games are the past, present, and future of artificial intelligence. In 1948, Alan Turing, one of the founding fathers of computer science and artificial intelligence, handwrote a program for chess. Today we have IBM's Deep Blue and DeepMind's AlphaGo, and huge efforts go into developing AI that can play such arcade games as Pac-Man. Programmers continue to use games to test and develop AI, creating new benchmarks for AI while also challenging human assumptions and cognitive abilities. Game design is at heart a cognitive science, Togelius reminds us—when we play or design a game, we plan, think spatially, make predictions, move, and assess ourselves and our performance. By studying how we play and design games, Togelius writes, we can better understand how humans and machines think. AI can do more for game design than providing a skillful opponent. We can harness it to build game-playing and game-designing AI agents, enabling a new generation of AI-augmented games. With AI, we can explore new frontiers in learning and play.

Machine Learning: ECML 2002

Tapio Elomaa,Heikki Mannila,Hannu Toivonen
Machine Learning ECML 2002 Book PDF

Author : Tapio Elomaa,Heikki Mannila,Hannu Toivonen
Publisher : Springer
Page : 538 pages
File Size : 53,5 Mb
Release : 2003-08-02
Category : Computers
ISBN : 9783540367550

Get Book

Machine Learning: ECML 2002 by Tapio Elomaa,Heikki Mannila,Hannu Toivonen Pdf

This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002. The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.

Deep Learning and the Game of Go

Kevin Ferguson,Max Pumperla
Deep Learning and the Game of Go Book PDF

Author : Kevin Ferguson,Max Pumperla
Publisher : Simon and Schuster
Page : 611 pages
File Size : 40,6 Mb
Release : 2019-01-06
Category : Computers
ISBN : 9781638354017

Get Book

Deep Learning and the Game of Go by Kevin Ferguson,Max Pumperla Pdf

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

Learning to Play

Aske Plaat
Learning to Play Book PDF

Author : Aske Plaat
Publisher : Springer Nature
Page : 330 pages
File Size : 42,7 Mb
Release : 2020-12-23
Category : Computers
ISBN : 9783030592387

Get Book

Learning to Play by Aske Plaat Pdf

In this textbook the author takes as inspiration recent breakthroughs in game playing to explain how and why deep reinforcement learning works. In particular he shows why two-person games of tactics and strategy fascinate scientists, programmers, and game enthusiasts and unite them in a common goal: to create artificial intelligence (AI). After an introduction to the core concepts, environment, and communities of intelligence and games, the book is organized into chapters on reinforcement learning, heuristic planning, adaptive sampling, function approximation, and self-play. The author takes a hands-on approach throughout, with Python code examples and exercises that help the reader understand how AI learns to play. He also supports the main text with detailed pointers to online machine learning frameworks, technical details for AlphaGo, notes on how to play and program Go and chess, and a comprehensive bibliography. The content is class-tested and suitable for advanced undergraduate and graduate courses on artificial intelligence and games. It's also appropriate for self-study by professionals engaged with applications of machine learning and with games development. Finally it's valuable for any reader engaged with the philosophical implications of artificial and general intelligence, games represent a modern Turing test of the power and limitations of AI.

The Devil Notebooks

Laurence A. Rickels
The Devil Notebooks Book PDF

Author : Laurence A. Rickels
Publisher : U of Minnesota Press
Page : 397 pages
File Size : 52,6 Mb
Release : 2008
Category : Literary Criticism
ISBN : 9780816650514

Get Book

The Devil Notebooks by Laurence A. Rickels Pdf

Milton's Paradise Lost. Goethe's Faust. Aaron Spelling's Satan's School for Girls? Laurence A. Rickels scours the canon and pop culture in this all-encompassing study on the Devil. Continuing the work he began in his influential book The Vampire Lectures, Rickels returns with his trademark wit and encyclopedic knowledge to go mano a mano with the Prince of Darkness himself.

Artificial Intelligence for Computer Games

John David Funge
Artificial Intelligence for Computer Games Book PDF

Author : John David Funge
Publisher : CRC Press
Page : 160 pages
File Size : 51,8 Mb
Release : 2004-07-29
Category : Computers
ISBN : 9781439864807

Get Book

Artificial Intelligence for Computer Games by John David Funge Pdf

Learn to make games that are more fun and engaging! Building on fundamental principles of Artificial Intelligence, Funge explains how to create Non-Player Characters (NPCs) with progressively more sophisticated capabilities. Starting with the basic capability of acting in the game world, the book explains how to develop NPCs who can perceive, remem

AI for Game Developers

David M Bourg,Glenn Seemann
AI for Game Developers Book PDF

Author : David M Bourg,Glenn Seemann
Publisher : "O'Reilly Media, Inc."
Page : 392 pages
File Size : 50,8 Mb
Release : 2004-07-23
Category : Computers
ISBN : 9781449333102

Get Book

AI for Game Developers by David M Bourg,Glenn Seemann Pdf

Written for the novice AI programmer, this text introduces the reader to techniques such as finite state machines, fuzzy logic, neural networks and many others in an easy-to-understand language, supported with code samples throughout the text.

Machine Learning: ECML 2003

Nada Lavrač
Machine Learning ECML 2003 Book PDF

Author : Nada Lavrač
Publisher : Springer Science & Business Media
Page : 521 pages
File Size : 54,7 Mb
Release : 2003-09-12
Category : Computers
ISBN : 9783540201212

Get Book

Machine Learning: ECML 2003 by Nada Lavrač Pdf

This book constitutes the refereed proceedings of the 14th European Conference on Machine Learning, ECML 2003, held in Cavtat-Dubrovnik, Croatia in September 2003 in conjunction with PKDD 2003. The 40 revised full papers presented together with 4 invited contributions were carefully reviewed and, together with another 40 ones for PKDD 2003, selected from a total of 332 submissions. The papers address all current issues in machine learning including support vector machine, inductive inference, feature selection algorithms, reinforcement learning, preference learning, probabilistic grammatical inference, decision tree learning, clustering, classification, agent learning, Markov networks, boosting, statistical parsing, Bayesian learning, supervised learning, and multi-instance learning.

Artificial Intelligence and Games

Georgios N. Yannakakis,Julian Togelius
Artificial Intelligence and Games Book PDF

Author : Georgios N. Yannakakis,Julian Togelius
Publisher : Springer
Page : 337 pages
File Size : 49,7 Mb
Release : 2018-02-17
Category : Computers
ISBN : 9783319635194

Get Book

Artificial Intelligence and Games by Georgios N. Yannakakis,Julian Togelius Pdf

This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.

Machine Learning, Animated

Mark Liu
Machine Learning Animated Book PDF

Author : Mark Liu
Publisher : CRC Press
Page : 465 pages
File Size : 49,5 Mb
Release : 2023-10-30
Category : Computers
ISBN : 9781000964776

Get Book

Machine Learning, Animated by Mark Liu Pdf

The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. Machine Learning, Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize, adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step, to the final converged parameters and predictions. This book teaches readers to create their own neural networks with dense and convolutional layers, and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning, witnessing AI achieve super-human performance in Atari games such as Breakout, Space Invaders, Seaquest and Beam Rider. Written in a clear and concise style, illustrated with animations and images, this book is particularly appealing to readers with no background in computer science, mathematics or statistics. Access the book's repository at: https://github.com/markhliu/MLA

Introduction to Machine Learning

Ethem Alpaydin
Introduction to Machine Learning Book PDF

Author : Ethem Alpaydin
Publisher : MIT Press
Page : 468 pages
File Size : 41,9 Mb
Release : 2004
Category : Computers
ISBN : 0262012111

Get Book

Introduction to Machine Learning by Ethem Alpaydin Pdf

An introductory text in machine learning that gives a unified treatment of methods based on statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining.

Reinforcement Learning

Marco Wiering,Martijn van Otterlo
Reinforcement Learning Book PDF

Author : Marco Wiering,Martijn van Otterlo
Publisher : Springer Science & Business Media
Page : 638 pages
File Size : 40,7 Mb
Release : 2012-03-05
Category : Technology & Engineering
ISBN : 9783642276453

Get Book

Reinforcement Learning by Marco Wiering,Martijn van Otterlo Pdf

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.

General Video Game Artificial Intelligence

Diego Pérez Liébana,Simon M. Lucas,Raluca D. Gaina,Julian Togelius,Ahmed Khalifa,Jialin Liu
General Video Game Artificial Intelligence Book PDF

Author : Diego Pérez Liébana,Simon M. Lucas,Raluca D. Gaina,Julian Togelius,Ahmed Khalifa,Jialin Liu
Publisher : Springer Nature
Page : 177 pages
File Size : 52,7 Mb
Release : 2022-05-31
Category : Mathematics
ISBN : 9783031021220

Get Book

General Video Game Artificial Intelligence by Diego Pérez Liébana,Simon M. Lucas,Raluca D. Gaina,Julian Togelius,Ahmed Khalifa,Jialin Liu Pdf

Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.