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7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
AI for Dynamic Difficulty in Games
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Early work
Interactive installations Stories that users participate in Interacting as expression
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Fall 1999
AAAI Narrative Intelligence Symposium Students from Parsons/NYU RE:Play
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
The Wheel
Set in a prison Rigid structure? Narrative – monolog & notes Factional
Actions result in global change Persistence = consequence Consequence = drama!
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Too Big
Lots of great ideas Erving Goffman Character and Personality Disorders NPR for emotional impact
Needed to graduate someday
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
2000
GDC Flexbot Build a mod… “Fix” multiplayer experience
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Ghostbot
Gladiator fiction Patrons donate items to favorites As long as you have one… …you can live!
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Sucked!
Bots: “Like White On Rice” Novice players
Live longer … seemingly forever
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
2001
Game Design & Tuning Workshop MDA of Multiplayer
Challenge Sensation Drama
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Oops!
Knee-capped multiplayer Removed challenge Rewarded failures Flattened the tension arc
…probably easy for experts to “game”
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Design Tools at Work
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Multiplayer Revisited
Fun because it’s people Training up = part of the challenge Frustration is still a factor Why do we keep playing?
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Challenge
Too Difficult
Too Easy
FlowChannel
LowSkill
HighSkill
increasing skill
incr
easi
ng
ch
alle
ng
e
M. Csikszentmihalyi
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Training
New tasks
Simple Goals
FlowChannel
Beginner skills
Skill increase
increasing skill
incr
easi
ng
ch
alle
ng
e
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Tennis
Backhand?
Beat Your Boss?
FlowChannel
Hit the ball?
Volley for 3 hours in hot sun?
increasing skill
incr
easi
ng
ch
alle
ng
e
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Engagement = Cyclical
Each challenge = new flow channel trip Understand and control those cycles?
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Opponent Process Theory
Comfort (steady state) is discouraged Sitting cross-legged “Pins and Needles”
Applied to vision, emotion, body chemistry
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Failure
Success
10sec.
10min.
1hr.
10hrs.time
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Flux vs. Flow
Regulating this feedback Engineering chaos, then calm Keeps the player “engaged”
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Game Difficulty
Typically static at run-time Flow happens – but only for a niche
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Experiencing Flow
How can we expand the flow channel? Include “just folks” and “gamers” alike? How can AI help?
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Adjusting Game Difficulty
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
FPS as a Base Case
Obstacle
Enemy
Search
Object
Spawn
Win (or retreat)
Die
Fight
FindFind
Solve (or not)
Get (or not)
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Goal
Avoid “flailing”:
flailing = repeatedly edging towards a state where current means do not support necessary and immediate ends.
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Inventory Theory
Flow In Flow OutInventory Level
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Basic Steps
Notice when a player is flailing Determine which changes can be made Execute changes as seamlessly as possible
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
In A Nutshell
Look at Player Inventory Current obstacles Performance over time
Generate projected probability of failure Adjust accordingly
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
AI View of this Process
Game Play Session
User Model
Action Planner
observations
actions
conditions
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Dynamic Systems View
Game Play Session
State Estimator
Control Policy
observations
actions
states
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Estimation
Estimate probability of getting hit Average measurements over time Add a fudge factor to value new estimates
over old ones
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Control
Regulator keeps system within a specified range low varience
Tracking System keeps the system within a range that changes
over time high varience
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Hamlet
Half Life/Case Closed mod Monitor game statistics Predict failure/death Define adjustment actions and policies Execute those actions and policies
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Game Chart
Some C# and C++ widgets Display data Play session traces “Knobs” to “Frob”
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Aesthetic Goals
Ramping challenge Responsive reward Sense of mastery
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Existing Dynamics
Enemies increasing number increasing strength increasing accuracy increasingly variable behavior increasingly “intelligent” or tactical behavior Increased frequency of surprise attacks
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Tweakable Mechanics
Available health Available ammunition Enemy Type/HP/Accuracy Weapon Type/Strength/Accuracy # of Targets Distance
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Other Considerations
Terrain/Lighting/Cover Group Movement Player’s Accuracy/Progress Player’s internal state
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Two Simple Policies
Novice case Expert case Scale between them?
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Novice Policy
“Comfort Zone” Regulator Babysitter Trial and error
Steady supply, consistent demand
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Expert Policy
“Discomfort Zone” Tracking System Boxing coach or Drill Sergeant Ramping challenge
Sporadic supply, high but erratic demand
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Could you do better?
Best policies? More robust policies? Other factors?
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
“Even a little better is better”
10% less work
10% more fun
... or both!
7.26.04 AAAI WorkshopChallenges in Game AI
Robin HunickeNorthwestern University
Thanks
Ian & NWU crew Michael, Phoebe and NI/CTP crew Looking Glass Mafia
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