The Number One Educational Resource for the Game Industry
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Overview:
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Neural networks have long been viewed with skepticism in game AI. However, there are times when their use is not only appropriate, but a powerful and time-saving approach, particularly for small teams with limited resources. This lecture will explain how 'Race for the Galaxy', a digital adaptation of the board game, uses temporal difference learning to power its AI. This knowledge-free system requires no human input to generate training data, which allows it to improve by playing against itself. Through this approach, the Temple Gate Games team was able to dramatically improve the challenge level offered by AI opponents without the significant time investment typical of tuning complex AI.
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