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An Application of Markov chain: Card shuffling and measuring the randomness of a deck

We investigate the card shuffling problem from a simulation-based approach. We first create a randomness measure for gauging how well-shuffled a deck is. Several hundred thousand random decks are generated to simulate the distribution of the randomness measures of well-shuffled decks. Then we examine the number of shuffles a certain shuffling scheme would take to reach the mean of this simulated distribution.

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Orego: Artificial Intelligence and the Game of Go

Go (Weiqi), the oldest strategy game in the world, was invented in China thousands of years ago. Its rules are simpler than those of Chess, but its strategies more subtle and profound. Top human Go players, unlike Chess players, can still easily defeat the most powerful computers. The space of possible board configurations is unfathomably vast, many orders of magnitude larger than the number of electrons in the universe. We suspect that human Go strength depends on the ability to decompose the game into local subproblems that are largely, but not quite, independent.

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