Sensorless but not senseless: Prediction in evolutionary car racing

Hugo Marques, Julian Togelius, Magdalena Kogutowska, Owen Holland, Simon M. Lucas

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper we try to develop predictors in order to drive a simulated car around a track without the most recent sensor data. In order to test the predictive abilities of our car we developed two experiments: one where the sensor data was interrupted for a certain time and another where the sensor data is constantly delayed by a certain amount. The predictors are based on neural networks, and we compare backpropagation and evolutionary computation as methods of training these. In the end we found that predictors with good driving performance do not sample the set of predictors which minimize the prediction error in the sensors.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007
    Pages370-377
    Number of pages8
    DOIs
    StatePublished - Sep 25 2007
    Event1st IEEE Symposium on Artificial Life, IEEE-ALife'07 - Honolulu, HI, United States
    Duration: Apr 1 2007Apr 5 2007

    Publication series

    NameProceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007

    Other

    Other1st IEEE Symposium on Artificial Life, IEEE-ALife'07
    CountryUnited States
    CityHonolulu, HI
    Period4/1/074/5/07

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    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Biochemistry, Genetics and Molecular Biology(all)

    Cite this

    Marques, H., Togelius, J., Kogutowska, M., Holland, O., & Lucas, S. M. (2007). Sensorless but not senseless: Prediction in evolutionary car racing. In Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007 (pp. 370-377). [4218909] (Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007). https://doi.org/10.1109/ALIFE.2007.367819