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Learning Game AI Programming with Lua

By : David Young
Book Image

Learning Game AI Programming with Lua

By: David Young

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Learning Game AI Programming with Lua
David Young
Nov, 2014 | 352 pages
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Table of Contents (16 chapters)
Learning Game AI Programming with Lua
Learning Game AI Programming with Lua
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Getting Started with AI Sandbox
Getting Started with AI Sandbox
Introduction to AI sandbox
Summary
2
Creating and Moving Agents
Creating and Moving Agents
Creating a new sandbox project
Setting up the file structure
Extending the SandboxApplication class
Running your sandbox for the first time
Creating a new Decoda project
Configuring Decoda's run executable
Creating a sandbox Lua script
Shooting blocks
Creating an agent Lua script
Agent properties
Physics
Knowledge
Agents' movement
Agent-steering forces
Avoidance
Avoiding blocks and agents
Group steering
Creating a group of followers
Summing steering forces
Summary
3
Character Animations
Character Animations
Skeletons and meshes
Attaching meshes to bones
Animation clips
Soldier poses
Manipulating animations
Animation blending
Animation state machine (ASM)
Building a weapon animation state machine
Building a soldier animation state machine
Updating animation state machines
Playing with states
Summary
4
Mind Body Control
Mind Body Control
Creating a body
Adding callbacks to the animation state machine
Getting our soldier to shoot
Getting our soldier to run
Creating a brain
Direct animation control
A simple, finite state machine
Indirect animation control
Running the obstacle course
Action latency
Summary
5
Navigation
Navigation
Pathfinding
Creating a navigation mesh
Pathfinding on a navigation mesh
The path information
Adding random pathfinding to our soldier
Creating additional navigation meshes
Summary
6
Decision Making
Decision Making
Creating userdata
Agent actions
Creating actions
Evaluators
Creating evaluators
Decision structures
Decision trees
Building a decision tree
Creating a decision tree agent
Finite state machines
Building a finite state machine
Creating a finite state machine agent
Strengths of finite state machines
Pitfalls of finite state machines
Behavior trees
Actions
Conditions
Selectors
Sequences
Creating a behavior tree object
Building a behavior tree
Creating a behavior tree agent
Strengths of behavior trees
Pitfalls of behavior trees
Summary
7
Knowledge Representation
Knowledge Representation
Knowledge sources
Blackboards
Creating soldier knowledge sources
Constructing a soldier blackboard
Updating decision evaluators
Updating behavior actions
Summary
8
Perception
Perception
Events
Managing events
Creating agent senses
Agent visibility
Agent sighting events
Handling new agent sightings
Agent auditory senses
Auditory events
Handling auditory events
Decaying blackboard events
Decaying auditory events
Team communications
Updating agent behaviors
Summary
9
Tactics
Tactics
Influence maps
Constructing an influence map
Drawing influence maps
Accessing influences
Clearing influences
Spreading influences
Influence map layers
Updating the influence map
Soldier tactics
Scoring team influences
Scoring dangerous areas
Summary
Index
Index

Strengths of behavior trees

Compared to decision trees, behavior tree actions know very little about actions other than the priority they show up in the tree. This allows for actions to be modular in nature and can reduce the need to rebalance a complex tree when more actions are added.

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