Games as Information Systems with Uncertainty “rules” schemas on content and discernability

COSC 4126 information and uncertainty Information theory – analysis of coding and capacity  coding systems have a capacity e.g., one byte has 256 configurations so can represent a ‘vocabulary’ of 256 distinct messages  messages contain more or less information depending on how much uncertainty they remove Are you at home?yes (1 out of 2) What day of the week is it? Thursday (1 out 7) 1

COSC 4126 information and uncertainty Information theory matching capacity to need: Are you at home? yes (1 out of 2) 1 bit – 2 messages What day of the week is it? Thursday (1 out 7) 3 bits – 8 messages Weaver “information is a measure of one’s freedom of choice when one selects a message”

COSC 4126 information and uncertainty Information theory  redundancy: measure of excess capacity Are you at home? “YES” (three character string) in ASCII: 24 bits, 1 bit info, 23 bits redundant  redundancy allows for error checking and correction (eg checksum bits) noise...  written language is redundant text messaging: jargon reduces redundancy, IMHO

COSC 4126 information and uncertainty Information theory in games  output is redundant but not a problem of information  input problems capacity coding redundancy

COSC 4126 information and uncertainty Information input  example - Brackeen’s game choices , , space, esc code of meaning (InputManager) capacity based on sequences of choices a language for the player to use: “ , , , ,space, , , , , , ,esc”

COSC 4126 information and uncertainty Information-based games  Mastermind  Twenty Questions (binary search) reducing uncertainty by narrowing choices

COSC 4126 information and uncertainty Signal transmission and noise  information transmission model information source transmitterdestinationreceiver signal received signal noise source message

COSC 4126 information and uncertainty Noise and redundancy  Noise alters a message  If a message has redundancy, the altered message can be identified, perhaps corrected

COSC 4126 information and uncertainty Noise-based games  Telephone circle  Charades noisy communication channels

COSC 4126 information and uncertainty Redundancy-based game  crossword puzzles most letters in the puzzle are over-specified by both a vertical and horizontal clue, though clues are (intentionally) noisy

COSC 4126 information and uncertainty Inputs and information transmission  (raw) mouse actions (left, right, down, up, click, double click)  (raw) keyboard input  component selection sets (menu, radio button, slider)  textfield coding, capacity, noise, redundancy e.g., adding the ‘deke’

COSC 4126 information and uncertainty Information theory – knowledge  information as game content - data and structure  meaning the “stuff” that can be encoded, transmitted, corrupted, received AND hidden, forgotten, learned, reorganized, acquired, memorized,... e.g. playing cards can reveal or conceal information 2

COSC 4126 information and uncertainty Knowledge categories of games  Perfect information – all players know complete state of the game e.g., chess, backgammon, monopoly  Imperfect information – players do not know complete state of game most card games, battleship, minesweeper, adventure games

COSC 4126 information and uncertainty Categories of information in games (Pearce, 1997) 1.Known to all players  board position 2.Known to only one (some) player(s)  hand of cards 3.Known to no players  draw pile 4.Randomly generated  throw of dice

COSC 4126 information and uncertainty Games based on information changing categories  card games – information is revealed to players  learning information known to no players is a focus of many digital games – Myst (data), Sims (principles)

COSC 4126 information and uncertainty digital games and information  powerful manipulation of information hidden processes, not just data reorganization of information information tools for the player (views, pause, snapshots, organizers)

COSC 4126 information and uncertainty Combining information 1 and 2  Enchanted Forest (handout) information as knowledge information as function of uncertainty

COSC 4126 information and uncertainty Uncertainty in games All games have uncertainty  Bernard deKoven, 1978: “Imagine how you would feel if, before the game, you were already declared the winner. Imagine how purposeless the game would feel.”  Why are sports televised live? 3

COSC 4126 information and uncertainty Uncertainty in games All games have uncertainty  without uncertainty, a player’s action cannot have meaning  uncertainty about game outcome is related to at uncertainty (?)in moves: actionresultgame outcome change of state ? die chess ? discernible? pit integration

COSC 4126 information and uncertainty Uncertainty in games Epstein, 1977: For a move or a game, the player can feel: 1.certainty – result known 2.risk – probabilities of results known in advance 3.uncertainty – no idea of outcome e.g.roulette – move: risk, night at casino: uncertainty chess - move: ceertainty, game uncertainty

COSC 4126 information and uncertainty Uncertainty and randomness  uncertainty does not require randomness chinese checkers middle game (result of complexity) tic-tac-toe NOT  uncertainty produces fun/motivation, opportunity for emergence chinese checkers multi-step jump

COSC 4126 information and uncertainty Randomness: using probability  constituative factor: probability distributions  operational factor: how is random result generated?

COSC 4126 information and uncertainty Pure chance games  Chutes and Ladders – where is the fun? operational rules – the actual activity moves have risk but outcome is uncertain:  chutes and ladders produce sudden reversals  end game delays front runner (compare with chinese checkers)

COSC 4126 information and uncertainty Pure chance games  Lotteries operational rules include constituatively meaningless choices (pick numbers, scratch) that acquire cultural meaning by operationalizing

COSC 4126 information and uncertainty Fallacies about probability Typical game players will misunderstand expected value  overvalue longshots misunderstand independent events and exclusive events  believe in the “law of averages,” so runs of failure make success more likely  believe rare bad events won’t recur but rare positive ones will overemphasize good outcomes believe in luck