search-adversarial-2up

search-adversarial-2up - 1 Artificial Intelligence CS4365...

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Unformatted text preview: 1 Artificial Intelligence CS4365 --- Spring 2009 a Adversarial Search Reading: Sections 6.1-6.4, R&N 2 Game Playing An AI Favorite • structured task • not initially thought to require large amounts of knowledge • focus on games of perfect information 3 Game Playing Initial State is the initial board/position Successor Function defines the set of legal moves from any position Terminal Test determines when the game is over Utility Function gives a numeric outcome for the game 4 Game Playing as Search 5 Partial Search Tree for Tic-Tac-Toe 6 • High values are good for MAX and bad for MIN. It is MAX’s job to use the search tree and utility values to determine the best move. • Root is initial position. Next level are all moves player 1 (MAX) can make; tree is from Max’s viewpoint. Next level are all possible responses from player 2 (MIN). • Max has to find a strategy that will lead to a winning terminal state regardless of what Min does. Strategy has to include the correct move for Max for each possible move by Min. 7 Simple Minimax 8 Simplified Minimax Algorithm 1. Expand the entire tree below the root. 2. Evaluate the terminal nodes as wins for the minimizer or maximizer. 3. Select an unlabeled node, n , all of whose children have been assigned values. If there is no such node, we’re done — return the value assigned to the root....
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This note was uploaded on 07/02/2009 for the course CS 4365 taught by Professor Vincent during the Spring '09 term at Universidad Torcuato Di Tella.

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search-adversarial-2up - 1 Artificial Intelligence CS4365...

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