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The Backgammon Machine Think Syndrome

By: tcads

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Would backgammon have stayed a board game had it not been for the computer? It is a good question, one that has since passed into obscurity, as the computer has superseded the traditional board game of backgammon. That is not to say that people still don’t huddle around a wooden board on a busy street corner cafe ?, or across an oak table with a warm fire burning behind them, moving their wooden pieces from point to point with obvious affection, to the accompaniment of a rolling dice.

The echoes of tradition resonate throughout the game, even to a certain extent in the virtual world. Yet progress in the computer age has moved backgammon on and is now a very hot topic for the web gaming devotee. The always on, never tiring opponent, offers a fresh challenge to players 24 hours a day, with what would seem an inexhaustible supply of players to compete against.

Out of this development has sprung a research programme that goes beyond simple game play. Extending its reach into what can best be described as artificial intelligence, or 'Does the machine think syndrome'? This stems from the self taught backgammon-playing computer programs, which are so good that they challenge many of the methods in which the game is played, especially in the opening gambit of the game. This has meant that players who play regularly against the machine, can only improve as the machine teaches them the better moves to make. In other words, their level of play improves.

Backgammon programs are entirely self taught and use the technique of reinforcement learning. It is the way we as humans learn, by rewarding when we do things right and chastising when we do things wrong. Because a machine or program is neutral, its aim is always to maximise the reward it receives. This doesn’t mean it gets an equivalent to a choc drop that you’d give a dog, rather it receives a numerical award based on the player’s most recent action.

This learning by lessons illustrates the ability that the program has to adapt to what it has learnt and is a part of what is best described as the learning curve.

But it still can't make the tea; not yet.

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