Artificial Intelligence


All the game has in terms of AI is the random number generator that picks the next piece to enter the play-field. However, the game mechanics are such that this random number is enough to completely change each game, presenting players with unique challenges after every piece is dropped. Since the randomness ensures that players never know what the next piece will be, they are forced to play the piece in a way that is optimal for whatever one of the seven pieces comes along next . (Many incarnations of Tetris include a next feature, which shows players the next piece that will come onto the play-field, a feature that does make the game a bit easier. Even when using this, however, players still do not know what the next-next-piece will be, hence they are still just making an educated guess as to where to stick the currently falling block.) If gameplay is about opposition , meaning an opponent providing a challenge to which players must react , and if in solitary computer games that opponent is the computer, then the fact that a random number generator provides all the challenge in Tetris demonstrates an important point. The AI the players face only needs to be as smart as the game mechanics require. An AI needs to present players with a situation that will challenge them, and it really does not matter how the AI establishes that challenge. It could be as complicated as the AI for a deep strategy game like Civilization , or it could be as simple as the random piece picker found in Tetris . What matters is that the AI matches up with the game mechanics to sufficiently challenge players.

The random nature in which pieces arrive at the top of the screen might suggest to the reader that success at Tetris is just luck. If the pieces players get are random, how can different players scores be compared against one another? The key point to realize here is that, over time, the randomness of the pieces evens out. Just as die rolls in a board game even out over the course of the game, the random pieces passed to players in Tetris end up functioning as if they were not random at all. Since there are only seven types of pieces, none with more than four blocks, and since players (at least initially) have a large space in which to manipulate them, the randomness keeps the game from becoming predictable while still making one player s game comparable to another s. Over the course of a game, players will get a few hundred pieces. The number of times players get just the piece they were looking for is evened out by the times they do not get the piece they want. It may be that players will fail to get exactly the right piece at the right time and that, since the box is already full of pieces, the game ends as a result. However, in order to get to a situation where they could not use whatever piece was given to them, players have already made a number of mistakes. In the end, the random piece picker found in Tetris provides a fair, consistent challenge to all players.




Game Design Theory and Practice
Game Design: Theory and Practice (2nd Edition) (Wordware Game Developers Library)
ISBN: 1556229127
EAN: 2147483647
Year: 2005
Pages: 189

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