Motocross and Artificial Neural Networks

Motocross and Artificial Neural Networks
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越野摩托车和人工神经网络

DOI:
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发表时间:
2005
期刊:
影响因子:
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通讯作者:
C. Fyfe
C. Fyfe
中科院分区:
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文献类型:
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作者:
Benoit Chaperot;C. Fyfe

文献摘要

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In this paper, we investigate training artificial neural networks to ride simulated motorbikes in a new computer game using two different training techniques, Evolutionary Algorithms and the Backpropagation Algorithm. We show that the backpropagation algorithm creates a rider which is faster than that created by the evolutionary algorithm but at the price of requiring a training set created by a human playing the game. Also the evolutionary algorithm has the advantage that it can find solutions which no human has previously found. Both methods create human-like performance in the motocross game.