Using a Genetic Algorithm to Weight an Evaluation Function for Tetris

Tetris is a popular video-game invented by Alexey Pajitnov. An agent that plays Tetris must be able to place pieces in good positions without knowledge of what pieces will follow. One way such an agent can work is to use an evaluation function to place the current piece. This evaluation function is a weighted sum of features from the board. We used a genetic algorithm, based on Genitor, to discover these weights. We tried several things to improve the efficiency of the search for the weights, including different fitness evaluations and crossover operations.