Julian Togelius – författare
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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.
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677 kr
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This book covers artificial intelligence methods applied to games, both in research and game development. It is aimed at graduate students, researchers, game developers, and readers with a technical background interested in the intersection of AI and games. The book covers a range of AI methods, from traditional search, planning, and optimization, to modern machine learning methods, including diffusion models and large language models. It discusses applications to playing games, generating content, and modeling players, including use cases such as level generation, game testing, intelligent non-player characters, player retention, player experience analysis, and game adaptation. It also covers the use of games, including video games, to test and benchmark AI algorithms. The book is informed by decades of research and practice in the field and combines insights into game design with deep technical knowledge from the authors, who have pioneered many of the methods and approaches used in the field.
This second edition of the 2018 textbook captures significant developments in AI and gaming over the past 7 years, incorporating advancements in computer vision, reinforcement learning, deep learning, and the emergence of transformer-based large language models and generative AI. The book has been reorganized to provide an updated overview of AI in games, with separate sections dedicated to AI’s core uses in playing and generating games, and modeling their players, along with a new chapter on ethical considerations. Aimed at readers with foundational AI knowledge, the book primarily targets three audiences: graduate or advanced undergraduate students pursuing careers in game AI, AI researchers and educators seeking teaching resources, and game programmers interested in creative AI applications. The text is complemented by a website featuring exercises, lecture slides, and additional educational materials suitable for undergraduate and graduate courses.
Computer Games
Fourth Workshop on Computer Games, CGW 2015, and the Fourth Workshop on General Intelligence in Game-Playing Agents, GIGA 2015, Held in Conjunction with the 24th International Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 26-27, 2015, Revised Selected Papers
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471 kr
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This book presents the most up-to-date coverage of procedural content generation (PCG) for games, specifically the procedural generation of levels, landscapes, items, rules, quests, or other types of content. Each chapter explains an algorithm type or domain, including fractal methods, grammar-based methods, search-based and evolutionary methods, constraint-based methods, and narrative, terrain, and dungeon generation.
The authors are active academic researchers and game developers, and the book is appropriate for undergraduate and graduate students of courses on games and creativity; game developers who want to learn new methods for content generation; and researchers in related areas of artificial intelligence and computational intelligence.Computer Games
5th Workshop on Computer Games, CGW 2016, and 5th Workshop on General Intelligence in Game-Playing Agents, GIGA 2016, Held in Conjunction with the 25th International Conference on Artificial Intelligence, IJCAI 2016, New York, USA, July 9-10, 2016, Revised Selected Papers
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734 kr
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458 kr
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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.
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