Automatic System Identification Based on Coevolution of Models and Tests
Created by W.Langdon from
gp-bibliography.bib Revision:1.8120
- @InProceedings{Koos:2009:cec,
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author = "Sylvain Koos and Jean-Baptiste Mouret and
Stephane Doncieux",
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title = "Automatic System Identification Based on Coevolution
of Models and Tests",
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booktitle = "2009 IEEE Congress on Evolutionary Computation",
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year = "2009",
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editor = "Andy Tyrrell",
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pages = "560--567",
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address = "Trondheim, Norway",
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month = "18-21 " # may,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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isbn13 = "978-1-4244-2959-2",
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file = "P255.pdf",
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DOI = "doi:10.1109/CEC.2009.4982995",
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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.",
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keywords = "genetic algorithms, genetic programming",
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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