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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 18 th in class , PRINTED!
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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: • 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 study
“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
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
feedback output adjustment Elements of a Cybernetic System“The feedback Loop” Environment Sensor Comparator Activator • AC-unit-in-a-room example • Heater-unit-in-a-room example
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
Game state feedback Scoring function output adjustment Game Controller Game mechanical bias • Information known to all players • Information known to only one player • Information known to the game only • Randomly generated information Game state Feedback Loops in Games(Marc LeBlanc) Environment Sensor Comparator Activator
Example of negative Feedback: Downforce • Negative: • Simulated momentum vs. player • AI lets itself catch-up if you are loosing • AI catches up if you are winning http://www.youtube.com/watch?v=z-OQzqUdbs4 http://www.youtube.com/watch?v=37g5uNwmqz4
AI lets itself catch-up if you are loosing • Position of autos • Configuration of track • … feedback Game state Scoring function • Player position, leadingCar position • Formally: Distance(player,finish), Distance(leadingCar,finish) adjustment output Game mechanical bias Game Controller • Slow down leading-car • Formally: • speed(leadingCar) • speed(player) f(Distance(player, leadingCar) • Player loosing? Formally: • Distance(player, finish) > Distance(leadingCar, finish)
Simulated gravity vs player control • Position of autos • Configuration of track • speed… feedback Game state Scoring function • Player direction • Road direction adjustment output Game mechanical bias Controller • Steer car towards road • Player going out of road?
Mortal Combat: combo • Health Points player • Health points opponent • Disabled (Yes, No) • Opponent situation (chance for next combo, no chance) Game state feedback Scoring function • Disabled, • Opponent situation adjustment output Controller Game mechanical bias • Disabled = Yes • Opponent situation = chance for next combo • Disabling attack
Using Feedback Loops: Difficulty LevelsBrigette 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) Examples? • 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!
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