Artificial Intelligence for Games / Edition 1

Artificial Intelligence for Games / Edition 1

by Ian Millington
     
 

ISBN-10: 0124977820

ISBN-13: 9780124977822

Pub. Date: 05/31/2006

Publisher: Taylor & Francis

Creating robust artificial intelligence is one of the greatest challenges for game developers. The commercial success of a game is often dependent upon the quality of the AI, yet the engineering of AI is often begun late in the development process and is frequently misunderstood.

In this book, Ian Millington brings extensive professional experience to the

Overview

Creating robust artificial intelligence is one of the greatest challenges for game developers. The commercial success of a game is often dependent upon the quality of the AI, yet the engineering of AI is often begun late in the development process and is frequently misunderstood.

In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. A game developer since 1987, he was founder of Mindlathe Ltd., at the time the largest specialist AI company in gaming. Ian shows how to think about AI as an integral part of game play.

He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's CD-ROM contains a library of C++ source code and demonstration programs, and provides access to a website with a complete commercial source code library of AI algorithms and techniques.

Product Details

ISBN-13:
9780124977822
Publisher:
Taylor & Francis
Publication date:
05/31/2006
Series:
The Morgan Kaufmann Series in Interactive 3D Technology Series
Edition description:
BK & DVD
Pages:
896
Product dimensions:
7.84(w) x 9.28(h) x 1.48(d)

Table of Contents

AI and Games
Introduction
What Is AI?
Model of Game AI
Algorithms, Data Structures, and Representations
On the Website
Layout of the Book
Game AI
The Complexity Fallacy
The Kind of AI in Games
Speed and Memory
The AI Engine
Techniques
Movement

The Basics of Movement Algorithms
Kinematic Movement Algorithms
Steering Behaviors
Combining Steering Behaviors
Predicting Physics
Jumping
Coordinated Movement
Motor Control
Movement in the Third Dimension
Pathfinding

The Pathfinding Graph
Dijkstra
A*
World Representations
Improving on A*
Hierarchical Pathfinding
Other Ideas in Pathfinding
Continuous Time Pathfinding
Movement Planning
Decision Making

Overview of Decision Making
Decision Trees
State Machines
Behavior Trees
Fuzzy Logic
Markov Systems
Goal-Oriented Behavior
Rule-Based Systems
Blackboard Architectures
Scripting
Action Execution
Tactical and Strategic AI
Waypoint Tactics
Tactical Analyses
Tactical Pathfinding
Coordinated Action
Learning

Learning Basics
Parameter Modification
Action Prediction
Decision Learning
Naive Bayes Classifiers
Decision Tree Learning
Reinforcement Learning
Artificial Neural Networks
Board Games
Game Theory
Minimaxing
Transposition Tables and Memory
Memory-Enhanced Test Algorithms
Opening Books and Other Set Plays
Further Optimizations
Turn-Based Strategy Games

Supporting Technologies
Execution Management

Scheduling
Anytime Algorithms
Level of Detail
World Interfacing

Communication
Getting Knowledge Efficiently
Event Managers
Polling Stations
Sense Management
Tools and Content Creation

Knowledge for Pathfinding and Waypoint Tactics
Knowledge for Movement
Knowledge for Decision Making
The Toolchain
Designing Game AI
Designing Game AI

The Design
Shooters
Driving
Real-Time Strategy
Sports
Turn-Based Strategy Games
AI-Based Game Genres
Teaching Characters
Flocking and Herding Games
Appendix
Books, Periodicals, and Papers
Games

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