Inducing models of human control skills

  • Rui Camachol
Decision Trees
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1398)


A new model of human control skills is proposed and empirically evaluated. It is called the incremental correction model and is more adequate for reverse engineering human control skills than any other previously proposed models. The experimental results show a considerable increase in robustness of the controllers that use the new model. The new model also attenuates the problem of unbalanced classes, noticed already in previous experiments. By means of Parameterised Decision Trees, propositional learners are still usable within the new model's framework.

key words

behavioural cloning decision trees cognitive modeling 


  1. 1.
    R. Camacho. Laboratory note: On robustness tests of induced auto-pilots from single flight plan missions, Sept. 1994. Available from:≈tau.Google Scholar
  2. 2.
    R. Camacho. Laboratory note: Learning to turn: decision-trees to perform a levelled turn, Sept. 1995. Available from:≈tau.Google Scholar
  3. 3.
    R. Camacho.Laboratory note. an incremental correction model for reverse engineering human control skills, Oct. 1997. Available from:≈tau.Google Scholar
  4. 4.
    R. Camacho. Laboratory note. learning to turn: Parameterised decision trees to perform a levelled turn, June 1997. Available from:≈tau.Google Scholar
  5. 5.
    R. Camacho and D. Michie. Behavioural cloning: a correction. AI Magazine, 16(2):92, Summer 1995.Google Scholar
  6. 6.
    A. A. Covrigaru and R. K. Lindsay. Deterministic autonomous systems. AI Magazine, 12(3):110–117, fall 1991.Google Scholar
  7. 7.
    J. C. Hamm. The use of pilot models in dynamic performance and rotor load prediction studies. In Proceedings of the Eighteenth European Rotorcraft Forum, pages 15–18, Avignon, Rance, September 1992. Association Aeronautique et Astronautique de France.Google Scholar
  8. 8.
    H. G. John, R. Kohavi, and K. Pfleger. Irrelevant features and the subset selection problem. In Machine Learning: Proceedings of the Eleventh International Conference, pages 121–129, Rutgers Univ., New Jersey, July 1994. eds. William Cohen and Haym Hirsh.Google Scholar
  9. 9.
    D. Michie and R. Camacho. Building symbolic representations of intuitive realtime skills from performance data. In Machine Intelligence 13, pages 385–418. Oxford University Press, Oxford, United Kingdom, 1994. eds. K. Furukawa, D. Michie and S. Muggleton.Google Scholar
  10. 10.
    C. Sammut, S. Hurst, D. Kedzier, and D. Michie. Learning to fly. In Proceedings of the Ninth International Workshop of Machine Learning 92, pages 385–393, Aberdeen, U.K., July 1992.Google Scholar
  11. 11.
    T. Urbančič and I. Bratko. Reconstructing human skill with machine learning. In The Eleventh European Conference on Artificial Intelligence, pages 498–502, Amsterdam, Netherlands, 1994.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Rui Camachol
    • 1
    • 2
  1. 1.LIACCPortoPortugal
  2. 2.FEUPPorto CodexPortugal

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