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Evolving ensembles of traffic lights controllers

Publication at Faculty of Mathematics and Physics |
2018

Abstract

We describe first results on a traffic-lights controller based on neural networks optimized by an evolutionary algorithm. Among the inputs of the neural network are outputs of other popular control algorithms, thus the evolved controller can be considered and ensemble controller.

In a series of experiments, we show that evolution is capable of creating controllers that provide promising performance better than any of a number of baselines.