Beating people at Scrabble is already no contest for computer programs, which can easily memorise entire dictionaries. Now a Scrabble-playing program has gone one better by playing dirty.
Developed by Eyal Amir and Mark Richards at the University of Illinois, Urbana-Champaign, the program is able to predict which letter tiles other players hold, and use this information to choose moves which block a high-scoring word that an opponent might otherwise have played. This aggressive gaming style gives it the edge over previous Scrabble programs, which focus solely on maximising their own scores.
To predict what tiles other players hold, Amir and Richards鈥檚 program begins by eliminating those tiles that have already been played. It then narrows down the possibilities by assuming that the tiles left on an opponent鈥檚 rack after they make a move do not include any letters that could have been used to form higher-scoring words than the word the opponent actually played. Adding in this 鈥渙pponent modelling鈥� greatly improved the program鈥檚 game, allowing it to beat Quackle, one of the best conventional Scrabble programs, by five points on average.
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Amir says his program can do more than simply beat its rivals. Because its play is more human-like than other Scrabble-bots, it could serve as a useful tool for training people to play against other people. He presented the bot at a conference on artificial intelligence in Hyderabad, India this week.
