General Video Game Artificial Intelligence

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General Video Game Artificial Intelligence
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Author : Diego Pérez Liébana
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2019-10-09
General Video Game Artificial Intelligence written by Diego Pérez Liébana and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-09 with Computers categories.
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.
General Video Game Artificial Intelligence
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Author : Diego Pérez Liébana
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
General Video Game Artificial Intelligence written by Diego Pérez Liébana and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Mathematics categories.
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 duringthese 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.
Artificial Intelligence And Games
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Author : Georgios N. Yannakakis
language : en
Publisher: Springer
Release Date : 2018-02-17
Artificial Intelligence And Games written by Georgios N. Yannakakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-17 with Computers categories.
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.
Playing Smart
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Author : Julian Togelius
language : en
Publisher: MIT Press
Release Date : 2019-01-15
Playing Smart written by Julian Togelius and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-15 with Games & Activities categories.
THE FUTURE OF GAME DESIGN IN THE AGE OF AI: Can games measure intelligence? And 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.
Ai For Games
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Author : Ian Millington
language : en
Publisher:
Release Date : 2021-10
Ai For Games written by Ian Millington and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10 with Artificial intelligence categories.
Game development lives in its own technical world. It has its own idioms, skills, and challenges. That's one of the reasons games are so much fun to work on. AI for Games is designed to help you understand one element of game development: artificial intelligence (AI).
Deep Learning And The Game Of Go
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Author : Kevin Ferguson
language : en
Publisher: Simon and Schuster
Release Date : 2019-01-06
Deep Learning And The Game Of Go written by Kevin Ferguson and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-06 with Computers categories.
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
Ai For Game Developers
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Author : David M. Bourg
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2004
Ai For Game Developers written by David M. Bourg and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
From the author of "Physics for Game Developers," comes a new, non-threatening introduction to the complex subject of game programming.
Computational Intelligence
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Author : Juan Julián Merelo
language : en
Publisher: Springer
Release Date : 2016-11-21
Computational Intelligence written by Juan Julián Merelo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Technology & Engineering categories.
This book includes a selection of revised and extended versions of the best papers from the seventh International Joint Conference on Computational Intelligence (IJCCI 2015), held in Lisbon, Portugal, from 12 to 14 November 2015, which was composed of three co-located conferences: The International Conference on Evolutionary Computation Theory and Applications (ECTA), the International Conference on Fuzzy Computation Theory and Applications (FCTA), and the International Conference on Neural Computation Theory and Applications (NCTA). The book presents recent advances in scientific developments and applications in these three areas, reflecting the IJCCI’s commitment to high quality standards.
Artificial Intelligence Games
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Author : Georgi Togeli
language : en
Publisher: A G Printing & Publishing
Release Date : 2024-09-03
Artificial Intelligence Games written by Georgi Togeli and has been published by A G Printing & Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-03 with Computers categories.
As has been pointed out by several industrial game AI developers the lack of behavioral modularity across games and in-game tasks is detrimental for the development of high quality AI [605, 171]. An increasingly popular method for ad-hoc behavior authoring that eliminates the modularity limitations of FSMs and BTs is the utility-based AI approach which can be used for the design of control and decision making systems in games [425, 557]. Following this approach, instances in the game get assigned a particular utility function that gives a value for the importance of the particular instance [10, 169]. For instance, the importance of an enemy being present at a particular distance or the importance of an agent’s health being low in this particular context. Given the set of all utilities available to an agent and all the options it has, utility-based AI decides which is the most important option it should consider at this moment [426]. The utility-based approach is grounded in the utility theory of economics and is based on utility function design. The approach is similar to the design of membership functions in a fuzzy set. A utility can measure anything from observable objective data (e.g., enemy health) to subjective notions such as emotions, mood and threat. The various utilities about possible actions or decisions can be aggregated into linear or non-linear formulas and guide the agent to take decisions based on the aggregated utility. The utility values can be checked every n frames of the game. So while FSMs and BTs would examine one decision at a time, utility-based AI architectures
Evolutionary Multi Criterion Optimization
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Author : Heike Trautmann
language : en
Publisher: Springer
Release Date : 2017-02-17
Evolutionary Multi Criterion Optimization written by Heike Trautmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Computers categories.
This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Münster, Germany in March 2017. The 33 revised full papers presented together with 13 poster presentations were carefully reviewed and selected from 72 submissions. The EMO 2017 aims to discuss all aspects of EMO development and deployment, including theoretical foundations; constraint handling techniques; preference handling techniques; handling of continuous, combinatorial or mixed-integer problems; local search techniques; hybrid approaches; stopping criteria; parallel EMO models; performance evaluation; test functions and benchmark problems; algorithm selection approaches; many-objective optimization; large scale optimization; real-world applications; EMO algorithm implementations.