Automatic System Identification Based on Coevolution of Models and Tests

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Koos:2009:cec,
  author =       "Sylvain Koos and Jean-Baptiste Mouret and 
                 Stephane Doncieux",
  title =        "Automatic System Identification Based on Coevolution
                 of Models and Tests",
  booktitle =    "2009 IEEE Congress on Evolutionary Computation",
  year =         "2009",
  editor =       "Andy Tyrrell",
  pages =        "560--567",
  address =      "Trondheim, Norway",
  month =        "18-21 " # may,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-2959-2",
  file =         "P255.pdf",
  DOI =          "doi:10.1109/CEC.2009.4982995",
  abstract =     "In evolutionary robotics, controllers are often
                 designed in simulation, then transferred onto the real
                 system. Nevertheless, when no accurate model is
                 available, controller transfer from simulation to
                 reality means potential performance loss. It is the
                 reality gap problem. Unmanned aerial vehicles are
                 typical systems where it may arise. Their locomotion
                 dynamics may be hard to model because of a limited
                 knowledge about the underlying physics. Moreover, a
                 batch identification approach is difficult to use due
                 to costly and time consuming experiments. An automatic
                 identification method is then needed that builds a
                 relevant local model of the system concerning a target
                 issue. This paper deals with such an approach that is
                 based on coevolution of models and tests. It aims at
                 improving both modeling and control of a given system
                 with a limited number of manipulations carried out on
                 it. Experiments conducted with a simulated quad rotor
                 helicopter show promising initial results about test
                 learning and control improvement.",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "CEC 2009 - A joint meeting of the IEEE, the EPS and
                 the IET. IEEE Catalog Number: CFP09ICE-CDR",
}

Genetic Programming entries for Sylvain Koos Jean-Baptiste Mouret Stephane Doncieux

Citations