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AI Game Development
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
SEO Network
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
SEO Блог
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
Index
→ Relish the
candy sweet bonanza
, a fusion of flavors
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