Temporal Difference Learning in the Tetris Game
نویسندگان
چکیده
Learning to play the game Tetris has been a common challenge on a few past machine learning competitions. Most have achieved tremendous success by using a heuristic cost function during the game and optimizing each move based on those heuristics. This approach dates back to 1990’s when it has been shown to eliminate successfully a couple hundred lines. However, we decided to completely depart from defining heuristics for the game and implement a “Know-Nothingism” approach, thereby excluding any human factor and therefore error/bias/pride in teaching the computer to play efficiently. Instead we use a combination of value iteration based on the Temporal Difference (TD) methodology in combination with a Neural Network to have the computer learn to play Tetris with minimal human interaction.
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تاریخ انتشار 2009