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?

Administrative: Game Design Analysis

• Deadline written document: November 18th in class, PRINTED!

• Deadline PowerPoint presentation: November 17th 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 minute

Administrative

• Test # 2: Friday November 8th. – It covers:

1. All of Unit 2 in the book2. 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

study

Games as Information Systems(Ch. 17)

“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 knowledge

• Under this view games put information at play• Classical Example:

The constitutive rules of poker can be viewed as a game where inference is made from imperfect information Another example

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)

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 play

Games as Cybernetic Systems (Ch. 18)

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-adjustment

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

adjustmentoutput

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 heater

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 before

Example of “this stuff” in games?

• Positive/negative feedback in games?

– An example of positive feedback

– An example of negative feedback

Feedback Loops in Games(Marc LeBlanc)

Environment

Comparator

Sensor

Activator

feedback

adjustmentoutput

Game state

Game mechanical bias

Scoring function

Game Controller

Game state

Information known to all playersInformation known to only one playerInformation known to the game onlyRandomly generated information

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 winning

AI lets itself catch-up if you are loosing

feedback

adjustmentoutput

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)

Simulated gravity vs player control

feedback

adjustmentoutput

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 road

Mortal Combat: combo

feedback

adjustmentoutput

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 attack

Using Feedback 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

progresses– Difficulty can be amount of

information available!– Dynamic Difficulty

Adjustment (DDA)

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?

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 ones

• Control:– Feedback systems can emerge from games– Feedback systems can take control away from gamers

… and result in lost of meaningful play!

Examples?

Announcement: Talk Tomorrow

"Building a science of narrative: Computational contributions to the study of stories and their telling"

R. Michael YoungProfessor, Department of Computer ScienceNorth Carolina State University

Tuesday, October 29, 4:00 PMLewis Lab Room 316