Recap From Previous Classes (I) Games as Schemes of Uncertainty –Macro-level: We don’t know outcome of game –Micro-level: Probability is assigned to outcome.

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Presentation transcript:

Recap From Previous Classes (I) Games as Schemes of Uncertainty –Macro-level: We don’t know outcome of game –Micro-level: Probability is assigned to outcome of actions Uniform distribution: all alternative events have the same probability (ex: rolling the dice in Chutes and Ladders) Non uniform distribution: some alternative events have a higher probability than others (ex: loot in an RPG game) –Expected Utility: a measure of how much I (the player) win from taking an action. It factors: Values of positive outcome and their probabilities Values of negative outcomes and their probabilities –Successful games have merged both micro-level and macro- level uncertainty

Recap From Previous Classes (II) Games as Schemes of Information Theory Systems Amount of information gained from an event is an inverse function of the probability of that event occurring Noise and Redundancy: 12 information -How much information 2 gained? -Was there any distortion (“noise”) while passing the information? 12 information -Noise: distortion in the communication 12 information -Redundancy: passing the same information by two or more different channels information

Games as Information Systems (Ch. 17)

Information: From Data to Knowledge DataSimple objects: john, Sebastian Relations: john is a parent of Sebastian Meta-relations: 1. Any parent of X is an ancestor of X 2. Any ancestor of a parent of X is an ancestor of X Abstract Concrete Knowledge Information

Perfect Information Games Does the player knows all information about the current state of the game?  Yes: perfect information game

Imperfect Information Games Does the player knows all information about the current state of the game?  No: imperfect information game

Do not Confuse “information” with “information” From the perspective of Information Theory (Ch. 16), information is a non-semiotic artifact Everywhere else (including now when we talk about Information Systems) we use “information” to refer 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

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 I)

Economy of Information Crucial game design question: how much information you going to show to the player. –Hiding information is a good way to caught players interest. Examples of a genre built around this? But, too much information, may make actions non discernable