Learning to Fly Simple and Robust

  • Dorian Šuc
  • Ivan Bratko
  • Claude Sammut
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3201)


We report on new experiments with machine learning in the reconstruction of human sub-cognitive skill. The particular problem considered is to generate a clone of a human pilot performing a flying task on a simulated aircraft. The work presented here uses the human behaviour to create constraints for a search process that results in a controller – pilot’s clone. Experiments in this paper indicate that this approach, called “indirect controllers”, results in pilot clones that are, in comparison with those obtained with traditional “direct controllers”, simpler, more robust and easier to understand. An important feature of indirect controllers in this paper is the use of qualitative constraints.


Regression Tree Control Rule Landing Gear Execution Trace Direct Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Dorian Šuc
    • 1
  • Ivan Bratko
    • 1
  • Claude Sammut
    • 2
  1. 1.Faculty of Computer and Information ScienceUniversity of LjubljanaLjubljanaSlovenia
  2. 2.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia

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