Author: | Micael DaGraca | ISBN: | 9781787129467 |
Publisher: | Packt Publishing | Publication: | June 30, 2017 |
Imprint: | Packt Publishing | Language: | English |
Author: | Micael DaGraca |
ISBN: | 9781787129467 |
Publisher: | Packt Publishing |
Publication: | June 30, 2017 |
Imprint: | Packt Publishing |
Language: | English |
Jump into the world of Game AI development
This book is for game developers with a basic knowledge of game development techniques and some basic programming techniques in C# or C++.
The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to determine character movement. Next, you'll learn how AI characters should behave within the environment created.
Moving on, you'll explore how to work with animations. You'll also plan and create pruning strategies, and create Theta algorithms to find short and realistic looking game paths. Next, you'll learn how the AI should behave when there is a lot of characters in the same scene.
You'll explore which methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions. You'll discover how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you think differently about AI.
The book has a step-by-step tutorial style approach. The algorithms are explained by implementing them in #.
Jump into the world of Game AI development
This book is for game developers with a basic knowledge of game development techniques and some basic programming techniques in C# or C++.
The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to determine character movement. Next, you'll learn how AI characters should behave within the environment created.
Moving on, you'll explore how to work with animations. You'll also plan and create pruning strategies, and create Theta algorithms to find short and realistic looking game paths. Next, you'll learn how the AI should behave when there is a lot of characters in the same scene.
You'll explore which methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions. You'll discover how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you think differently about AI.
The book has a step-by-step tutorial style approach. The algorithms are explained by implementing them in #.