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You're reading from Unity 5.x Game AI Programming Cookbook

Product type Book

Published in Mar 2016

Publisher Packt

ISBN-13 9781783553570

Pages 278 pages

Edition 1st Edition

Languages

Concepts

Game Artificial Intelligence

Author (1):

Jorge Palacios

Table of Contents (15) Chapters

Unity 5.x Game AI Programming Cookbook

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

1. Behaviors – Intelligent Movement

Introduction
Creating the behavior template
Pursuing and evading
Arriving and leaving
Facing objects
Wandering around
Following a path
Avoiding agents
Avoiding walls
Blending behaviors by weight
Blending behaviors by priority
Combining behaviors using a steering pipeline
Shooting a projectile
Predicting a projectile's landing spot
Targeting a projectile
Creating a jump system

2. Navigation

Introduction
Representing the world with grids
Representing the world with Dirichlet domains
Representing the world with points of visibility
Representing the world with a self-made navigation mesh
Finding your way out of a maze with DFS
Finding the shortest path in a grid with BFS
Finding the shortest path with Dijkstra
Finding the best-promising path with A*
Improving A* for memory: IDA*
Planning navigation in several frames: time-sliced search
Smoothing a path

3. Decision Making

Introduction
Choosing through a decision tree
Working a finite-state machine
Improving FSMs: hierarchical finite-state machines
Combining FSMs and decision trees
Implementing behavior trees
Working with fuzzy logic
Representing states with numerical values: Markov system
Making decisions with goal-oriented behaviors

4. Coordination and Tactics

Introduction
Handling formations
Extending A* for coordination: A*mbush
Creating good waypoints
Analyzing waypoints by height
Analyzing waypoints by cover and visibility
Exemplifying waypoints for decision making
Influence maps
Improving influence with map flooding
Improving influence with convolution filters
Building a fighting circle

5. Agent Awareness

Introduction
The seeing function using a collider-based system
The hearing function using a collider-based system
The smelling function using a collider-based system
The seeing function using a graph-based system
The hearing function using a graph-based system
The smelling function using a graph-based system
Creating awareness in a stealth game

6. Board Games AI

Introduction
Working with the game-tree class
Introducing Minimax
Negamaxing
AB Negamaxing
Negascouting
Implementing a tic-tac-toe rival
Implementing a checkers rival

7. Learning Techniques

.Introduction
Predicting actions with an N-Gram predictor
Improving the predictor: Hierarchical N-Gram
Learning to use Naïve Bayes classifiers
Learning to use decision trees
Learning to use reinforcement
Learning to use artificial neural networks
Creating emergent particles using a harmony search

8. Miscellaneous

Introduction
Handling random numbers better
Building an air-hockey rival
Devising a table-football competitor
Creating mazes procedurally
Implementing a self-driving car
Managing race difficulty using a rubber-banding system

Index

Introduction

In this chapter, you will learn about a family of algorithms for developing board game techniques to create artificial intelligence. They are based on the principle of a game tree (graph) that spans as we evaluate a state and decide to visit its neighbors. They also take into account board games for two rivals. But with a little bit of work, some of them can be extended to more players.