06-adversarial_search - Game Playing Foundations of...

Info icon This preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
1 Foundations of Artificial Intelligence Adversarial Search CS472 – Fall 2007 Thorsten Joachims Game Playing An AI Favorite structured task clear definition of success and failure does not require large amounts of knowledge (at first glance) focus on games of perfect information 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 Game Playing as Search x Partial Search Tree for Tic-Tac-Toe x x x x x x x x x x x o o o o o o o o o o o o o o o x x x x x x x x x x x x x x x x x x x o MIN(O) MAX(X) MIN(O) TERMINAL UTILITY MAX(X) 0 +1 -1 Simplified Minimax Algorithm 1. Expand the entire tree below the root. 2. Evaluate the terminal nodes as wins for the minimizer or maximizer (i.e. utility). 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. 4. If n is a minimizer move, assign it a value that is the minimum of the values of its children. If n is a maximizer move, assign it a value that is the maximum of the values of its children. Return to Step 3.
Image of page 1

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon