First Steps toward Automated Design of Mechatronic Systems Using Bond Graphs and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{kisungseo:2001:gecco,

• title = "First Steps toward Automated Design of Mechatronic Systems Using Bond Graphs and Genetic Programming",
• author = "Kisung Seo and Erik D. Goodman and Ronald C. Rosenberg",
• pages = "189",
• year = "2001",
• publisher = "Morgan Kaufmann",
• booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001)",
• 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",
• address = "San Francisco, California, USA",
• publisher_address = "San Francisco, CA 94104, USA",
• month = "7-11 " # jul,
• keywords = "genetic algorithms, genetic programming: Poster, bond graphs, dynamic systems design, mechatronic, systems design",
• ISBN = "1-55860-774-9",
• URL = "http://garage.cse.msu.edu/papers/GARAGe01-07-03.pdf",
• URL = "http://citeseer.ist.psu.edu/445817.html",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco2001/d02.pdf",
• size = "1 page",
• 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.",
• 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