Chapter 4 (Add) - Artificial Intelligence Chapter 4 Games...

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Artificial Intelligence Chapter 4: Games in AI
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Why do games attract interest of computer scientists? Seemed to be a good domain for work on machine intelligence, because games were thought to: provide a source of a good structured task in which success or failure is easy to measure.
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Example: Chess Number of possible unique chess games is 10 120 . In 1957 , artificial intelligence pioneers Herbert Simon and Allen Newell predicted that a computer would beat a human at chess within 10 years . BELLE , a chess program by Ken Thompson and Joe Condon, became the first computer to be awarded the title of US chess master, in 1983 . (26 + 1957) BELLE didn’t try to do what a human would do. Instead, BELLE took advantage of what computers do well. In May 1997 (40 + 1957) , IBM's Deep Blue Supercomputer played a fascinating match with the reigning World Chess Champion, Garry Kasparov and won 3 ½ to 2 ½ .
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Reduction to Search Playing chess seems complicated. Computational thinking suggests transforming ( reducing ) it into something that computers do well: search State of games is easy to represent. Too hard to solve.
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The Simple Case Chess, Checkers, Go, Mancala, Tic-Tac-Toe, Othello, Nim, … Two players alternate moves Zero-sum : one player’s loss is another’s gain Perfect Information : each player knows the entire game state Deterministic : no element of chance/randomness Clear set of legal moves Well-defined outcome (e.g. win, lose, draw)
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More complicated games Most card games (e.g. Hearts, Bridge, etc.) and Scrabble non-deterministic lacking in perfect information. Cooperative games Real-time strategy games (lack alternating moves). e.g. Warcraft
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2-player, zero-sum, discrete, finite, 2-player, zero-sum, discrete, finite, deterministic, games of perfect deterministic, games of perfect information information What does it means? Two player: :-) Zero-sum: In any outcome of any game, Player A’s gains equal player B’s losses. Discrete: All game states and decisions are discrete values. Finite: Only a finite number of states and decisions. Deterministic: No chance (no die rolls). Perfect information: Both players can see the state, and each decision is made sequentially (no simultaneous moves).
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10 2-player zero-sum discrete finite 2-player zero-sum discrete finite deterministic games of perfect deterministic games of perfect information information
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2-player zero-sum discrete finite 2-player zero-sum discrete finite deterministic games of perfect deterministic games of perfect information information Not Finite Stochastic One Player Mutiplayer Hidden Information Involves Animal Behave Two Players
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Types of Games Chess, Checkers Go, Othello Backgammon, Monopoly Battleship Bridge, Poker, Scrabble, Nuclear war Deterministic Chance Perfect Information Imperfect Information
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Computer Games Chess – Deep Blue (World Champion 1997) Checkers – Chinook (World Champion 1994) Othello – Logistello Beginning, middle, and ending strategy
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  • Winter '14
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  • Game Theory, Max, Minimax, alpha-beta pruning

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