Practical game AI programming : create game AI and implement cutting edge AI algorithms from scratch / Micael DaGraça.

Format:

Book

Author/Creator:

DaGraça, Micael, author.

Language:

English

Subjects (All):

Artificial intelligence.

Physical Description:

1 online resource (1 volume) : illustrations

Edition:

1st edition

Place of Publication:

Birmingham, [England] ; Mumbai, [India] : Packt, 2017.

System Details:

text file

Biography/History:

DaGraca Micael: Micael DaGraca is a professional game designer and interactive creator who works with independent video game studios and creates interactive apps focused on the health and pharmaceutical industries. He studied digital arts at the University of IESA Multimedia, Paris, and ESAD Matosinhos. He started his career as a project manager in a small studio and then gradually started working as a game developer by helping other studios to develop their games. More recently, he has been creating interactive content for the pharmaceutical industry.

Summary:

Jump into the world of Game AI development About This Book Move beyond using libraries to create smart game AI, and create your own AI projects from scratch Implement the latest algorithms for AI development and in-game interaction Customize your existing game AI and make it better and more efficient to improve your overall game performance Who This Book Is For This book is for game developers with a basic knowledge of game development techniques and some basic programming techniques in C# or C++. What You Will Learn Get to know the basics of how to create different AI for different type of games Know what to do when something interferes with the AI choices and how the AI should behave if that happens Plan the interaction between the AI character and the environment using Smart Zones or Triggering Events Use animations correctly, blending one animation into another and rather than stopping one animation and starting another Calculate the best options for the AI to move using Pruning Strategies, Wall Distances, Map Preprocess Implementation, and Forced Neighbours Create Theta algorithms to the AI to find short and realistic looking paths Add many characters into the same scene and make them behave like a realistic crowd In Detail 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. Style and approach The book has a step-by-step tutorial style approach. The algorithms are explained by implementing them in #.

Contents:

Cover

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Table of Contents

Preface

Chapter 1: Different Problems Require Different Solutions

A brief history of and solutions to game AI

Enemy AI in video games

From simple to smart and human-like AI

Visual and audio awareness

Summary

Chapter 2: Possibility and Probability Maps

Game states

Possibility maps

How to use possibility maps

Preparing a possibility map (FPS)

Creating a possibility map (FPS)

Defining the states

DEFENSIVE state

AGGRESSIVE state

Possibility map conclusion

Probability maps

How to use probability maps

Where to go from here

Chapter 3: Production System

Automated finite-state machines (AFSMs)

Calculating chances

Utility-based functions

Dynamic game AI balancing

Chapter 4: Environment and AI

Visual interactions

Basic environment interactions

Moving environment objects

Obstructive environment objects

Breaking down the environment by area

Advanced environment interactions

Adapting to unstable terrain

Using raycast to evaluate decisions

Chapter 5: Animation Behaviors

2D animation versus 3D animation

2D animation - sprites

3D animation - bone structure

The main differences

Animation state machines

Smooth transitions

Chapter 6: Navigation Behavior and Pathfinding

Navigation behavior

Choosing a new direction

Avoid walking against walls

Choosing an alternative path

Point to point movement

Tower defense genre

Racing genre

MOBA genre

Point to point movement and avoiding dynamic objects

Chapter 7: Advanced Pathfinding

Simple versus advanced pathfinding

A* search algorithm

How it works

Disadvantages of using A*.

Going directly from A to B

From point A to B with obstacles in the way

Generating grid nodes

Pathfinding implementation

Chapter 8: Crowd Interactions

What is crowd interaction

Video games and crowd interactions

Assassin's Creed

Grand Theft Auto (GTA)

The Sims

FIFA/Pro evolution soccer

Planning crowd interactions

Group fight

Communication (attention zones)

Communication (talking to other AI characters)

Team sports

Crowd collision avoidance

Chapter 9: AI Planning and Collision Avoidance

Search

Offensive search

Predicting opponent actions

Collision avoidance

Chapter 10: Awareness

Stealth sub-genre

About tactics

About awareness

Implementing vision awareness

Basic vision detection

Advanced vision detection

Realistic field of view effect

Index.

Notes:

Includes index.

Description based on online resource; title from PDF title page (ebrary, viewed October 19, 2017).

OCLC:

995052702