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The implementation of two popular graph traversal algorithms, a-star and minimax with alpha-beta pruning, in the context of artificial intelligence. A-star is a widely used path-finding method, while minimax with alpha-beta pruning is a recursive algorithm used for determining the best course of action in two-player games. The theory behind each algorithm and sample code for implementation.
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A Star Algorithm: One of the best and most widely used methods for path-finding and graph traversals is the A* Search algorithm. Minimax algorithm with alpha beta pruning: With the assumption that the opposing player is likewise playing optimally, the recursive algorithm minimax is used to determine a player's best course of action. It is used in numerous two-player games, including tic-tac-toe, go, chess, Isola, checkers, and many others. Because it is possible to view every action that could be made in a certain game, these games are also known as games of perfect information. Alpha-beta pruning removes (prunes) all the nodes that might not be influencing the final decision from a standard minimax algorithm, returning the same move as the normal one.