Presentation on theme: "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."— Presentation transcript:
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! 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! –Dont improvise, dont wait until the last minute
Administrative Test # 2: Friday November 8 th. –It covers: 1.All of Unit 2 in the book 2.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 Dont 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 exampleexample
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 feedbackadjustment output
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 feedbackpositive –An example of negative feedbacknegative
Feedback Loops in Games ( Marc LeBlanc) Environment Comparator Sensor Activator feedbackadjustment 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 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 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)
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 road
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 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 Young Professor, Department of Computer Science North Carolina State University Tuesday, October 29, 4:00 PM Lewis Lab Room 316