First Steps toward Automated Design of Mechatronic Systems Using Bond Graphs and Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{kisungseo:2001:gecco,
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title = "First Steps toward Automated Design of Mechatronic
Systems Using Bond Graphs and Genetic Programming",
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author = "Kisung Seo and Erik D. Goodman and
Ronald C. Rosenberg",
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pages = "189",
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year = "2001",
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publisher = "Morgan Kaufmann",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO-2001)",
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editor = "Lee Spector and Erik D. Goodman and Annie Wu and
W. B. Langdon and Hans-Michael Voigt and Mitsuo Gen and
Sandip Sen and Marco Dorigo and Shahram Pezeshk and
Max H. Garzon and Edmund Burke",
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address = "San Francisco, California, USA",
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publisher_address = "San Francisco, CA 94104, USA",
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month = "7-11 " # jul,
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keywords = "genetic algorithms, genetic programming: Poster, bond
graphs, dynamic systems design, mechatronic, systems
design",
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ISBN = "1-55860-774-9",
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URL = "http://garage.cse.msu.edu/papers/GARAGe01-07-03.pdf",
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URL = "http://citeseer.ist.psu.edu/445817.html",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2001/d02.pdf",
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size = "1 page",
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abstract = "This paper suggests a method for automatically
synthesizing designs for mechatronic systems. The
domain of mechatronic systems includes mixtures of, for
example, electrical, mechanical, hydraulic, pneumatic,
and thermal components, making it difficult to design a
system to meet specified performance goals with a
single design tool. Bond graphs are domain independent,
allow free composition, and are efficient for
classification and analysis of models, allowing rapid
determination of various types of acceptability or
feasibility of candidate designs (Karnopp et al). This
can sharply reduce the time needed for analysis of
designs that are infeasible or otherwise unattractive.
Genetic programming is well recognized as a powerful
tool for open-ended search (Koza et al). The
combination of these two powerful methods is therefore
an appropriate target for a better system for synthesis
of complex multi-domain systems. The approach described
here will evolve new designs (represented as bond
graphs) with ever-improving performance, in an
iterative loop of synthesis, analysis, and feedback to
the synthesis process.",
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notes = "GECCO-2001 A joint meeting of the tenth International
Conference on Genetic Algorithms (ICGA-2001) and the
sixth Annual Genetic Programming Conference (GP-2001)
Part of \cite{spector:2001:GECCO}",
- }
Genetic Programming entries for
Kisung Seo
Erik Goodman
Ronald C Rosenberg
Citations