Practical Game AI (give or take)

Practical Game AI (give or take) Dave Pottinger, President/CEO @dcpottinger www.bonusxp.com

What is this talk? • ½ AI Programming bits • ½ Designer-y stuff • ½ Hard/Fun/Sh*tty Lessons Learned • Q&A

WTF do I know? • Increasingly little;) • Making games since 1993 • Programmer, Designer, Reluctant Biz Guy

What is Practical Game AI? “…more what you’d call guidelines than actual rules.”

Buzzwords vs. Basics • Sexy • Genetic Algorithms • Neural Nets, Learning Code • Expert Systems • A* • Useful • Data driven code • Understandable, reusable code • Good team dev skills • A*

So, let’s design an AI! • Unit/Character vs. Player • Player AI Questions • Does it have to play a symmetric game? • Can it Cheat? Should it Cheat? • Difficulty levels? • Replayable? • Learning?

RTS Unit AI • Action system • Idle, Attack, Gather • Animation management • Player Commands • Entity Logic • Searching, Attack Response • Pathfinding & Movement • Player AI interface

RTS Player AI • Basics • Resource Gathering • Base Construction • Attacking • Advanced • Situational Response • Planning & Unit Coordination • Variety, Replay • Strategic Layers

OMFFFG, where do I start? • Play the Game • Blank files are scary, therefore… “Baby Steps”

Breadth Example: RTS Attacking • Attack components • Troops (which require buildings & resources) • Target • Path • Timing/Coordination • Difficulty level • Etc This is a HUGE task!

Breadth Example: RTS Attacking • TLDR: Fake everything;) • Phase 1: • Pre-placed troops • Specific target • TASK: Get the troops to attack the target

Breadth Example: RTS Attacking • Phase 2: • Pre-placed troops • Multiple targets • TASK: Data-drive the target priorities

Breadth Example: RTS Attacking • Phase 3: • Pre-placed buildings • Cheat the resources • TASK: Train the troops

Breadth Tidbits • Get an End Result ASAP • Designers must use it • Ingame debug display • Love the Iteration

Representation Example #1: Abstract Type System • Like hashtags • Blends base types and logical types • Lists are precomputed • Use everywhere • Searching • Research Prereqs

Representation Example #2:Resource Site Aggregation • Combine individual items • Done at load time • Makes AI play more “like a human” • Faster to search

Representation Example #3:Terrain Analysis • Make areas @ load • More “human”, etc. • Add data • Feed into Strategy

Managing the Player • Context Hook • Give Players a way to believe • They will fill in the gaps • Some randomness is important • No one likes to lose to an AI • Make them sweat • Create excuse options

General Advice • AI should be fun for players, not you • Build & Iterate, don’t Plan • Get it running quickly! • Build a good test harness

Programmer Advice #1 • Ideally, wait until the game is fun • Stick to what you know • 90% of effective AI is simple code • Everyone should do AI… Yay?

Programmer Advice #2 • Structure and Representation are the keys • Write defensive logic • Don’t be afraid to refactor • If you can’t recite A*, you’re doing it wrong

Design Advice • Learn how to program;) • Pick the team’s battles • Players will fill in the gaps • One exploit ruins everything • Exaggerate the AI

Side Effects of Good AI • You’ll find • Misplaced game logic • New & exciting ways to break the game • Performance problems • Hard to understand game systems • Multiplayer exploits • Automated Testing potential

Questions? Dave Pottinger, President/CEO @dcpottinger www.bonusxp.com

Practical Game AI (give or take)