딥러닝에 기반한 최신 AI 기술들은 음성 인식, 음성 합성, 번역, 챗봇, 스마트 팩토리 등 다양한 분야에서 활발하게 도입되고 있지만, 게임 분야에서는 아직 본격적인 적용 사례가 많지 않습니다. Springer에서 발간된 도서인 “Artificial Intelligence and Games”에서는 부분적이나마 게임 분야에서 활용 가능한 AI 기술들을 정리해서 소개하고 있습니다. 주요 목차는 다음과 같습니다:
Part I: Background
- Introduction
1.1 This Book
1.2 A Brief History of Artificial Intelligence and Games
1.3 Why Games for Artificial Intelligence
1.4 Why Artificial Intelligence for Games
1.5 Structure of This Book
1.6 Summary - AI Methods
2.1 General Notes
2.2 Ad-Hoc Behavior Authoring
2.3 Tree Search
2.4 Evolutionary Computation
2.5 Supervised Learning
2.6 Reinforcement learning
2.7 Unsupervised learning
2.8 Notable Hybrid Algorithms
2.9 Summary
Part II: Ways of Using AI in Games
- Playing Games
3.1 Why Use AI to Play Games?
3.2 Game Design and AI Design Considerations
3.3 How Can AI Play Games?
3.4 Which Games Can AI Play?
3.5 Further Reading
3.6 Exercises
3.7 Summary - Generating Content
4.1 Why Generate Content?
4.2 Taxonomy
4.3 How Could We Generate Content?
4.4 Role of PCG in Games
4.5 What Could Be Generated?
4.6 Evaluating Content Generators
4.7 Further Reading
4.8 Exercises
4.9 Summary - Modeling Players
5.1 What Player Modeling Is and What It Is Not
5.2 Why Model Players?
5.3 A High-Level Taxonomy of Approaches
5.4 What Is the Model’s Input Like?
5.5 What Is the Model’s Output Like?
5.6 How Can We Model Players?
5.7 What Can We Model?
5.8 Further Reading
5.9 Exercises
5.10 Summary
Part III: The Road Ahead
- Game AI Panorama
6.1 Panoramic Views of Game AI
6.2 How Game AI Areas Inform Each Other
6.3 The Road Ahead
6.4 Summary - Frontier Game AI Research
7.1 General General Game AI
7.2 AI in Other Roles for Games
7.3 Ethical Considerations
7.4 Summary
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