Raven

Robin Burke

GAM 376

Soccer standings

Burke, 7 Ingebristen, 6 Buer, 6 Bukk, 6 Krishnaswamy, 4 Lobes, 3 Borys, 2 Rojas, 2 Bieneman, 2

Playoff round

Bukk vs Buer, (12-1), 12-2.76 Bukk vs Ingebristen, (3-2), 3-4.32 Buer vs Ingebristen, (8-2), 8-2 Record 1-1-1 Tie-breaker

goals scored Buer 10.76 Ingebristen 6.32 Bukk 15

The Final!

Burke vs Bukk

Syllabus proposal

Current 11/6

• Goal-driven Behavior 11/8

• Goal and Behavior Lab 11/13

• Fuzzy Logic Proposal

11/6• Goal-driven Behavior

11/8• Fuzzy Logic

11/13• Machine Learning

Raven

Demo Controls

right-click to select• see what the bot is doing

right-click again to control• left click fires• right click selects destination• mouse controls firing direction• 1—4 weapon selection• X to release

Game architecture

Game objectsMap

• walls• triggers• spawn points• navigation graph

BotsWeaponsProjectiles

Triggers

Control game state changes Example

"health giver"• if a bot enters a certain region

• its health is increased Many other applications

button opens door, etc. weapon makes a sound

Every update cycle check to see if trigger has been activated apply its effects

Trigger code

AI Architecture I

What must a bot do?

High-level decision making

What should I do now?attackhideseek power upheal

Higher-level navigation

Given a locationpath to get to itbest path to get to it

A* search through the navigation graph

Low-level navigation

Don't run into walls, etc. Can be achieved with appropriate

steering behaviors

Perception

Makes a big difference in the playability of the game

NPCs do not have perceptual systems can theoretically know everything about the

game state sometimes this knowledge is needed to

compensate for their stupidity But

designer must be very judicious players can tell if the sensory system is

unfair

Examples

you approach silentlybut the enemy turns around anyway

you hidebut the enemy knows exactly where to

look you avoid the searchlight

but the guards shoot you anyway this is really annoying

Avoiding omniscience

Must construct a perceptual model for each agent

Model filters out data that the agent shouldn't perceive

Typically will model vision hearing pain memory

Nescience

Being blind is almost as bad as being omniscient

ExamplesYou can stand outside the door and

snipe• guard can't see you when you aren't in

the room

Guards walk right over fallen comrade

Avoiding ignorance

Sensory memorydon't forget what you just saw

Short-term location memorytrack "last seen" position of enemies

Use audio cueshearing a weapon fire gives position

information

Perception in Raven

Bots have 180 degree field of view Bots always know when a power-up is available Bots cannot see through walls

expensive calculation! Bots have a memory record

for each opponent records when and where last seen

Weapon firing generates an audio trigger propagated to nearby units gives away position of shooter

Target Selection

Who to shoot? Simple

shoot the closest Many other criteria could be used

shoot the weakest• RB_Bot

shoot the one who is attacking youetc.

Weapon Handling

When to shootnot instantlytoo tough

Where to shootnot totally accuratelysuperhuman

What to useweapon selection

Weapon Selection

Which weapon to select?blaster

• short range, low damageshotgun

• damage disperses with distancemissile launcher

• high damage, slow projectilerail gun

• low damage, instant, long distance

Updating

Cannot update all AI components all the time too expensive not necessary

Movement all the time

• don't run into walls Weapon Selection

less often Sensory Memory

infrequently requires checking visibility

Path Planning infrequently requires search

Systems

Steering Behaviors

Path Planning

Path Following

Decision Making

Weapon Selection

Target Selection

Part A of Lab