Received the information offered Interested Email me Any commentsdiscussion about the QampA session Do you think it was worthwhile Administrative Game Design Analysis Deadline written document ID: 254493
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Slide1
Q&A Session with Game Developer
Received the information offered.
Interested? E-mail me
Any comments/discussion about the Q&A session?
Do you think it was worthwhile?Slide2
Administrative: Game Design Analysis
Deadline
written document:
November 18
th
in class
,
PRINTED!
Deadline PowerPoint presentation:
November 17
th
until 6AM
(EST time) has to be e-mailed to
instructor
If
you haven't done so, start working on this now!
Don’t improvise, don’t wait until the last minuteSlide3
Administrative
Test # 2: Friday November 8
th
.
It covers:
All of Unit 2 in the book
All topics we covered in the lectures after Test # 1
Similar in style to Test #1
Meaning you really have to study (1) and (2) above
Idea: work on Game Design Analysis o help prepare for the test
Don’t improvise/wait for the last minute to studySlide4
Games as Information Systems
(Ch. 17)Slide5
“information
” in Information Systems
From the perspective of
Information Theory
(Ch. 16), information is a non-semiotic artifact
In contrast, for
Information Systems
, “
information”
has meaning. Includes everything from data to knowledgeUnder this view games put information at playClassical Example:
The constitutive rules of poker can be viewed as a game where inference is made from imperfect information
Another
exampleSlide6
Kinds of Information in a Game
Information known to all players
Information known to only one player
Information known to the game only
Randomly generated information
(
clip from Civilization
IV)Slide7
Economy of Information
Crucial game design question: how much information you
are going
to show to the
player?
Hiding information is a good way to caught players interest.
Example of hidden information that is revealed while playing:
State information in imperfect information games.
Fog of war
Plot
Adventure games
Player skills
RPG games
Rules of the game
Learning through playSlide8
Games as Cybernetic Systems (Ch. 18)Slide9
Cybernetics
Resulted from Information Theory (Ch. 16) and Information Systems Theory (Ch. 17
)
Focus on how dynamic systems change over
time
Cybernetics is used to study organizations
Large companies
Governments
Cybernetics is also used in Operations Research and Machine Learning
Basic principle: output-
feedback
-adjustmentSlide10
Elements of a Cybernetic System“The feedback Loop”
Environment
Comparator
Sensor
Activator
AC-unit-in-a-room
example
Heater-unit-in-a-room example
feedback
adjustment
outputSlide11
Kinds of Feedback
Example of each for the AC-unit-in-a-room example
Negative
: temperature(room) > 75
then activate
cooler
Positive
: temperature(room)
>
75
then activate
heaterSlide12
Simple Cybernetic Design
Lets combine two feedback loops that maintains the temperature in a room stays between 65
and 75
We have
an AC unit and
We have a
heater
Lets do one that maintains the temperature in a room at 70
. Same conditions as beforeSlide13
Example of “this stuff” in games?
Positive/negative feedback in games
?
An example of
positive
feedback
An example of
negative
feedbackSlide14
Feedback
Loops
in Games
(
Marc LeBlanc)
Environment
Comparator
Sensor
Activator
feedback
adjustment
output
Game state
Game mechanical bias
Scoring function
Game Controller
Game state
Information known to all players
Information known to only one player
Information known to the game only
Randomly generated informationSlide15
Example of negative Feedback: Downforce
http://www.youtube.com/watch?v=37g5uNwmqz4
http://www.youtube.com/watch?v=z-OQzqUdbs4
Negative:
Simulated
momentum vs
. player
AI lets itself catch-up if you are loosing
AI catches up if you are winningSlide16
AI lets itself catch-up if you are loosing
feedback
adjustment
output
Game state
Game mechanical bias
Scoring function
Game Controller
Position of autos
Configuration of track
…
Player loosing? Formally:
Distance(player, finish) > Distance(leadingCar, finish)
Player position, leadingCar position
Formally: Distance(player,finish), Distance(leadingCar,finish)
Slow down leading-car
Formally:
speed(leadingCar)
speed(player)
f(
Distance(player, leadingCar) Slide17
Simulated gravity vs player control
feedback
adjustment
output
Game state
Game mechanical bias
Scoring function
Controller
Position of autos
Configuration of track
speed…
Player going out of road?
Player direction
Road direction
Steer car towards roadSlide18
Mortal Combat: combo
feedback
adjustment
output
Game state
Game mechanical bias
Scoring function
Controller
Health Points player
Health points opponent
Disabled (Yes, No)
Opponent situation (chance for next combo, no chance)
Disabled = Yes
Opponent situation = chance for next combo
Disabled,
Opponent situation
Disabling attackSlide19
Using F
eedback Loops:
Difficulty Levels
Brigette
Swan
Adaptation to the quirks and habits of a particular player over
time: reinforcement learning
Many games implement difficulty sliders.
Common:
start early levels easy
More difficult as game progressesDifficulty can be
amount of information available!
Dynamic Difficulty Adjustment (DDA)Slide20
Dynamic Difficulty Adjustment (DDA)
-- The Oblivion Controversy
Idea: adjust game so that it remains challenging (negative feedback)
It is an RPG game like say Diablo but…
As your avatar levels so do all mobs in the game
So for example you “clean” a dungeon at level 1 killing some rats, at level 10 those rats will be armored and will hit much harder
Does it still have meaningful play as a result?Slide21
Use of Feedback in Games
(
Marc LeBlanc)
Stability
:
Negative feedback stabilizes a game
Positive feedback destabilizes a game
Game duration
Negative feedback can prolong a game
Positive feedback can end it
Success:Positive feedback magnifies early success
Negative feedback magnifies late onesControl:Feedback systems can emerge from gamesFeedback systems can take control away from gamers… and result in lost of meaningful play!
Examples?Slide22
Announcement: Talk Tomorrow
"Building a science of narrative: Computational contributions to the study of stories and their telling"
R. Michael Young
Professor, Department of Computer Science
North Carolina State University
Tuesday, October 29, 4:00 PM
Lewis Lab Room 316