Table of content

•	Table of Contents
•	Index

AI Game Development: Synthetic Creatures with Learning and Reactive Behaviors
By Alex J. Champandard
Publisher	: New Riders Publishing
Pub Date	: November 21, 2003
ISBN	: 1-5927-3004-3
Pages	: 744
				Copyright
		About the Author
		About the Technical Reviewers
		Acknowledgments
		Tell Us What You Think
		Foreword
			About Alex
			Something Different
			Useful for Everybody
		Introduction
			Why Learning and Reactive Behaviors?
			Who Is This Book For?
			How Is the Book Organized?
			Where Is the Web Site?
			Which Software Is Required?
		Part I:  Overview
			Chapter 1.  Artificial Intelligence in Computer Games
				Overview of Artificial Intelligence
				Computer Games and AI
				The State of Game AI
				Designers Versus AI
				AI in Game Programming
			Chapter 2.  The Design of Intelligence
				An Engineer's Perspective
				Traditional Approach
				A Modern Approach
				Required Background
				AI Development Process
				Summary
			Chapter 3.  Reactive Approach
				Definitions
				Behaviors: Planning Versus Reactive
				Reactive Techniques in Game Development
				Architectures
				Summary
			Chapter 4.  FEAR: A Platform for Experimentation
				Technical Overview
				World Interface
				Modules
				Flexible Architecture
				Creating an Animat
				Summary
		Part II:  Moving Around
			Chapter 5.  Movement in Game Worlds
				The Environment and Space
				Types of Game Worlds
				Handling Movement
				Assumptions
				Testing Conditions
				Summary
			Chapter 6.  Moving Abilities
				The Art of Navigation
				Game Bots and Movement
				Autonomous Navigation for Animats
				Criteria for Motion
				Case Study
				Summary
			Chapter 7.  Analysis and Understanding
				The Big Picture
				The Analysis Phase
				The Understanding Phase
				General Advice
				Summary
			Chapter 8.  Formalizing Motion
				Background Review
				Sketching Possible Options
				Rationalizing
				Proposed Specification
				Summary
			Chapter 9.  Specifications and Knowledge Representation
				Overview of Formal Specifications
				Knowledge Representation
				Knowledge Representation Formalisms
				Specification Procedure
				Discussion
				Summary
			Chapter 10.  Steering Behaviors for Obstacle Avoidance
				Artificial Life Overview
				Algorithm
				Original Draft
				Evaluation
				Summary
			Chapter 11.  Rule-Based Systems
				Background
				Overview of Components
				Theory and Knowledge
				Discussion
				Summary
			Chapter 12.  Synthesizing Movement with Rule-Based Systems
				Case Study
				Rationale
				RBS Module Design
				Implementation
				Application
				Evaluation
				Summary
			Part II.  Conclusion
				Retrospective Overview
				Outlook
		Part III:  Learn to Shoot!
			Chapter 13.  Combat Settings
				In the Armory
				Weapon Requirements
				Environment Conditions
				Training Zone
				Summary
			Chapter 14.  Player Shooting Skills
				The Art of Combat
				Gaming Skills
				Criteria for Shooting
				Case Study
				Summary
			Chapter 15.  Shooting, Formally
				Background
				Sketching Possible Options
				Rationalizing
				Proposed Specification
				Summary
			Chapter 16.  Physics for Prediction
				Foundations
				The Perfect Intersection
				Predicting Behavior
				Simulation Algorithm
				Experimentation
				Evaluation
				Summary
			Chapter 17.  Perceptrons
				History of Perceptrons
				Model Overview
				Simulation
				Introduction to Optimization
				Optimization of Perceptron Weights
				Training Procedure
				Graphical Interpretation
				Summary
			Chapter 18.  Dealing with Aiming Errors
				Momentum and Friction
				Dealing with Errors
				Evaluation
				Summary
			Chapter 19.  Multilayer Perceptrons
				History of Perceptrons
				Model Overview
				Simulation
				Biological Parallels
				Training Algorithms
				Practical Issues
				Discussion
				Summary
			Chapter 20.  Selecting the Target
				Case Study
				Rationale
				Module Design
				Implementation
				Application
				Evaluation
				Summary
			Chapter 21.  Knowledge of the Problem
				Black Box Understanding
				Underlying Knowledge
				Fundamental Understanding
				Refining the Problem
				Methodology
				Summary
			Part III.  Conclusion
				Retrospective Overview
				Outlook
		Part IV:  Choose Your Weapon
			Chapter 22.  Fighting Conditions
				Weapon Properties
				Applicability of Weapons
				Training Zone
				Summary
			Chapter 23.  Weapon Selection
				Appealing Choices
				Evaluation Process in Practice
				Criteria for Weapon Selection
				Case Study
				Summary
			Chapter 24.  Formalizing Weapon Choice
				Sketching Possible Options
				Rationalizing
				Proposed Specification
				Summary
			Chapter 25.  Scripting Tactical Decisions
				Foundations in Scripting
				Scripted Weapon Selection
				Evaluation
				Summary
			Chapter 26.  Classification and Regression Trees
				Representation of Decision Trees
				Classifying and Regressing
				Tree Induction
				Training Procedure
				Discussion
				Summary
			Chapter 27.  Learning to Assess Weapons
				Four Different Approaches
				Rationale
				Module Design
				Implementation
				Application
				Evaluation
				Summary
			Chapter 28.  Understanding the Solution
				Complexity of the Solution
				The Search Space
				Different Approaches to Finding a Solution
				Summary
			Part IV.  Conclusion
				Retrospective Overview
				Outlook
		Part V:  Using Items and Objects
			Chapter 29.  Analysis and Specification
				Objects in the World
				Behavior Enhancements
				Specification
				Summary
			Chapter 30.  Fuzzy Logic
				Set Logic Extended
				Fuzzy Representation and Conversions
				Fuzzy Logic
				Fuzzy Control and Decision Making
				Discussion
				Summary
			Chapter 31.  Enhancing Movement Behaviors with a Fuzzy System
				Fuzzy Variables and Membership Functions
				Fuzzy Rules
				Module Design
				Evaluation
				Summary
			Chapter 32.  Genetic Algorithms
				Biological Evolution in a Nutshell
				Genetics and Representation
				Genetic Algorithms
				Genetic Operators and Evolutionary Policies
				Advanced Issues
				Discussion
				Summary
			Chapter 33.  Learning Classifier Systems
				Representation of Classifiers
				Overview of the Classifier System
				Architecture
				Discussion
				Summary
			Chapter 34.  Adaptive Defensive Strategies with Genetic Algorithms
				Representation of Action Sequences
				Genetic Operators
				Evolutionary Outline
				Genetic Algorithm Module Design
				Computing the Fitness
				Application
				Evaluation
				Summary
			Chapter 35.  Designing Learning AI
				Purpose of Learning
				Approach to Learning
				Varieties of Learning Components
				Methodologies for Learning Behaviors
				Summary
			Part V.  Conclusion
				Retrospective Overview
				Outlook
		Part VI:  Emotions
			Chapter 36.  Emotive Creatures
				Emotions Within Human Evolution
				Biological Models for Emotion
				From Emotions to Artificial Intelligence
				Human/Machine Interaction
				Emotion in Games
				Summary
			Chapter 37.  Sensations, Emotions, and Feelings
				Sensations
				Emotions
				Interfaces for Communicating Emotions
				Portraying Emotions in Games
				Summary
			Chapter 38.  Finite-State Machines
				Formal Definitions
				Representation and Simulation
				Control Logic
				Optimization
				Discussion
				Summary
			Chapter 39.  Under the Influence
				Designing Artificial Emotions
				Finite-State Module Development
				Creating Emotions as Finite States
				Evaluation
				Summary
			Chapter 40.  Nondeterministic State Machines
				Overview
				Fuzzy State Machines
				Nondeterministic State Machines
				Probabilistic State Machines
				Summary
			Chapter 41.  Hierarchical State Machines
				Overview
				Hierarchies
				Interaction Semantics
				Discussion
				Summary
			Chapter 42.  An Emotional System
				Hierarchical Architecture Overview
				Modeling Feelings
				Improved Sensations
				Accumulating Emotions
				Revealing Emotions with Mannerisms
				Mood Hierarchies
				Evaluation
				Summary
			Chapter 43.  Emergent Complexity
				A Definition of Emergence
				Emergent Behaviors
				Smarter Environments, Simpler Behaviors
				Emergence in Functionality
				Summary
			Part VI.  Conclusion
				Retrospective Overview
				Outlook
		Part VII:  Action Selection
			Chapter 44.  Strategic Decision Making
				Game Situation
				Personal Objectives
				Tactical Behaviors
				Animats and Decision Making
				A Training Zone
				Summary
			Chapter 45.  Implementing Tactical Intelligence
				Crafting Tactical Behaviors
				Behaviors and the Subsumption Architecture
				Applying Subsumption to Tactics
				Evaluation
				Summary
			Chapter 46.  Learning Reinforcement
				Defining Reinforcement Theory
				Fundamental Elements
				Reinforcement Learning Algorithms
				Advanced Issues
				Discussion
				Summary
			Chapter 47.  Learning Reactive Strategies
				Decomposition by Control
				Adaptive Gathering Behaviors
				Modeling Movement
				Learning Shooting Styles
				Other Capabilities
				Evaluation
				Summary
			Chapter 48.  Dealing with Adaptive Behaviors
				What's the Problem?
				Solid Software Engineering
				Robust Design
				Methodologies
				Summary
			Part VII.  Conclusion
				Retrospective Overview
				Outlook
		Part VIII:  Summary
			Chapter 49.  Game AI Engineering Principles
				Architectures
				Implementations
				Techniques and Their Applicability
				Learning and Feedback Mechanisms
				Summary
			Chapter 50.  The Road Ahead
				Practice Makes Perfect
				On World Models
				Planning Techniques
				Embracing Nouvelle Game AI
		Bibliography
		Index