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Applied Intelligence
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TD-Gammon is a neural network that is able to teach itself toplay backgammon solely by playing against itself and learning fromthe results, based on the TD(») reinforcement learningalgorithm (Sutton 1988). Despite starting from random initialweights (and hence random initial strategy), TD-Gammon achieves asurprisingly strong level of play. With zero knowledge built in atthe start of learning (i.e., given only a "raw" description of theboard state), the network learns to play at a strong intermediatelevel. Furthermore, when a set of hand-crafted features is added tothe network's input representation, the result is a trulystaggering level of performance: the latest version of TD-Gammon isnow estimated to play at a strong master level that is extremelyclose to the world's best human players.