We describe an approach to creating a controller for The Open Car Racing Simulator (TORCS), based on The Simulated Car Racing Championship (SCRC) client, using unsupervised evolutionary learning for recurrent neural networks. Our method of training the recurrent neural network controllers relies on combining the components of the singular value decomposition of two different neural network connection matrices.
Training RNN simulated vehicle controllers using the SVD and evolutionary algorithms
2018 IEEE Intelligent Vehicles Symposium (IV) ; 1949-1953
2018-06-01
675796 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
TRAINING RNN SIMULATED VEHICLE CONTROLLERS USING THE SVD AND EVOLUTIONARY ALGORITHMS
British Library Conference Proceedings | 2018
|Optimizing traffic light controllers by means of evolutionary algorithms
Tema Archiv | 1998
|Selection and Tuning of Controllers by Evolutionary Algorithms: Application to Fast Ferries Control
British Library Conference Proceedings | 2005
|Robust acoustic vehicle body design using evolutionary algorithms
Tema Archiv | 2006
|