Part I: Background
1. Introduction
1.1 What Is This Book About?
1.2 A Brief History of Artificial Intelligence and Games
1.3 Why Use Games for Artificial Intelligence?
1.4 Why Use Artificial Intelligence for Games?
1.5 The AI and Games Co-revolution
1.6 Structure of This Book
1.7 Summary
2. AI Fundamentals
2.1 General Concepts
2.2 Search and Optimization
2.3 Machine Learning
2.4 AI and Human Feedback
2.5 Summary
3. AI Methods for Games
3.1 Behavior Authoring
3.2 Tree Search Methods
3.3 Local and Global Search Methods
3.4 Unsupervised Learning Methods
3.5 Supervised Learning Methods
3.6 Deep Learning Methods
3.7 Reinforcement Learning Methods
3.8 Summary
Part II: Play
4. Playing Games
4.1 Why Use AI to Play Games?
4.2 Taxonomy: Playing Games
4.3 Further Reading
4.4 Summary
5. Methods for Playing Games
5.1 Behavior Authoring
5.2 Planning-Based Approaches
5.3 Reinforcement Learning
5.4 Supervised Learning
5.5 Large Pretrained Models
5.6 Chimeric Game Players
5.7 Learning Beyond Policies
5.8 Further Reading
5.9 Summary
6. Gameplaying AI by Game Genre
6.1 Board Games
6.2 Card Games
6.3 Real-time 2D Video Games
6.4 Real-Time 3D Video Games
6.5 Dungeon Crawlers
6.6 Puzzle Games
6.7 Strategy Games
6.8 Text-Based Games
6.9 Social Simulation Games
6.10 Further Reading
6.11 Exercises
6.12 Summary
Part III: Generate
7. Procedural Content Generation
7.1 Why Generate Content?
7.2 Taxonomy: Procedural Content Generation
7.3 Further Reading
7.4 Summary
8. Methods for Generating Content
8.1 Constructive Methods
8.2 Evolutionary Algorithms and Search-Based PCG
8.3 Quality-Diversity Methods
8.4 Solver-Based Methods
8.5 PCG via Machine Learning
8.6 Reinforcement Learning
8.7 Further Reading
8.8 Summary
9. Procedural Content Generation by Content Type
9.1 Levels
9.2 Visuals
9.3 Audio
9.4 Narrative
9.5 Rules and Mechanics
9.6 Games
9.7 Evaluating Content Generators
9.8 Further Reading
9.9 Exercises
9.10 Summary
Part IV: Model
10. Player Modeling
10.1 Why Model Players?
10.2 What Is Player Modeling?
10.3 Taxonomy: Player Modeling
10.4 Further Reading
10.5 Summary
11. From Observations to Models of Players
11.1 What Is the Model’s Input Like?
11.2 What Is the Model’s Output Like?
11.3 Manual Labeling: Principles and Tools
11.4 Methods for Player Modeling
11.5 Further Reading
11.6 Summary
12. Player Modeling Exemplified
12.1 Player Embeddings
12.2 Player Behavior
12.3 Player Experience
12.4 Further Reading
12.5 Exercises
12.6 Summary
Part V: The Road Ahead
13. Panorama and Map of Synergies
13.1 Panoramic Views of AI and Games
13.2 How Game AI Areas Inform Each Other
13.3 What’s Next?
13.4 Summary
14. Frontiers of AI and Games Research
14.1 General General Game AI
14.2 Game Engines for Game AI
14.3 Other Uses and Roles of AI in Games
14.4 Summary
15. Ethics of AI and Games
15.1 Overview
15.2 Elicitation—Boundaries of Artificially Induced Emotions
15.3 Sensing—Privacy and Control
15.4 Detection—Transparency in Limited Information Systems
15.5 Adaptation—Ownership of Data and Models
15.6 Other Issues and Concerns
15.7 Summary