This book covers all the necessary topics that a professional game AI programmer needs to know, from math and steering behaviours to terrain analysis, pathfinding and decision-making. Written to be easily accessible, each topic is accompanied by an example game that allows the reader to add their own code to see the effects their changes have.
Each chapter is split into two parts. The first part covers the necessary theory in a friendly, conversational manner, using visual examples and fictional game scenarios to give additional context. The second part is a coding tutorial in C# for the topic at hand. Each chapter has its own example game available to download, written in C# in the Unity Game Engine.
This book will be suitable for students and aspiring games programmers looking to gain a grounding in game AI techniques.
Author(s): Paul Roberts
Publisher: CRC Pr I Llc
Year: 2022
Language: English
Commentary: True vector PDF
Pages: 302
Chapter 1: Introduction
About the Author
Who Is this Book for?
How to Read this Book
Accompanying Framework
What Is Game AI?
Game AI and Game Genres
Chapter 2: Math
What Is a Vector?
Dot Product
Rotation
Math – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 3: Steering Behaviours
Steering Forces
Combining Behaviours
Group Behaviours
Final Thoughts
Steering Behaviours – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 4: Terrain Analysis
Influence Maps
Heat Maps
Cell Granularity
Final Thoughts
Terrain Analysis – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 5: Pathfinding
Spatial Representation
Pathfinding
Final Thoughts
Pathfinding – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 6: Decision-Making
Finite State Machine
Fuzzy State Machine
Stack-Based FSM
Behaviour Trees
Final Thoughts
Decision-Making – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 7: Fuzzy Logic
Sets
Fuzzy Sets
Fuzzy Rules
Defuzzification
Final Thoughts
Fuzzy Logic – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 8: Chess AI
Minimax Algorithm
Alphabeta Pruning
Evaluation Functions
Final Thoughts
Chess AI – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 9: Genetic Algorithms
Initial Population
Encoding
Fitness
Selection
Crossover
Mutation
Final Thoughts
Genetic Algorithms – Practical
Project Overview
Step-By-Step Guide
Future Work
Chapter 10: Neural Networks
Biology
Single-Layer Perceptron
Multi-Layer Perceptron
Learning
Game Example: Snake
Final Thoughts
Neural Networks – Practical
Project Overview
Step-By-Step Guide
Future Work
Index
