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Unity 5.x Game AI Programming Cookbook

You're reading from   Unity 5.x Game AI Programming Cookbook Build and customize a wide range of powerful Unity AI systems with over 70 hands-on recipes and techniques

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Product type Paperback
Published in Mar 2016
Publisher Packt
ISBN-13 9781783553570
Length 278 pages
Edition 1st Edition
Tools
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Authors (2):
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Jorge Palacios Jorge Palacios
Author Profile Icon Jorge Palacios
Jorge Palacios
Jorge Elieser P Garrido Jorge Elieser P Garrido
Author Profile Icon Jorge Elieser P Garrido
Jorge Elieser P Garrido
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Toc

Table of Contents (15) Chapters Close

Unity 5.x Game AI Programming Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Behaviors – Intelligent Movement FREE CHAPTER 2. Navigation 3. Decision Making 4. Coordination and Tactics 5. Agent Awareness 6. Board Games AI 7. Learning Techniques 8. Miscellaneous Index

Representing states with numerical values: Markov system


Having learned about fuzzy logic, it may do us well to mix some approaches and probably extend the functionality with finite-state machines. However, fuzzy logic doesn't work directly with values—they have to be defuzzified before they have a meaning within its scope. A Markov chain is a mathematical system that allows us to develop a decision-making system that can be seen as a fuzzy state machine.

Getting ready

This recipe uses the matrix and vector classes that come with Unity to illustrate the theoretical approach and make a working example, but it can be improved with our own matrix and vector classes with the proper implementation of the required member functions, such as vector-matrix multiplication.

How to do it...

  1. Create the parent class for handling transitions:

    using UnityEngine;
    using System.Collections;
    
    public class MarkovTransition : MonoBehaviour
    {
        public Matrix4x4 matrix;
        public MonoBehaviour action;
    }
  2. Implement...

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