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@InProceedings{jianjunHu:2004:ACC, author = "Jianjun Hu and Erik Goodman and Ronald Rosenberg", title = "Topological search in automated mechatronic system synthesis using bond graphs and genetic programming", booktitle = "Proceedings of American Control Conference ACC 2004", year = "2004", volume = "6", pages = "5628--5634", month = jun # " 30-" # jul # " 2", organisation = "American Control Conference", address = "Boston, MA, USA", email = "hujianju@msu.edu", keywords = "genetic algorithms, genetic programming, bond graphs, control system synthesis, eigenvalues and eigenfunctions, inverse problems, mechatronics, search problems, automated mechatronic system synthesis, bond graphs, eigenvalue placement problem, encoding, inverse problem, open ended topology search, population seeding, scalable benchmark problem", ISBN = "0-7803-8335-4", URL = "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1384751", abstract = "We have introduced a well-defined scalable benchmark problem - the eigenvalue placement problem - to investigate scalability issues in automated topology synthesis of mechatronic systems based on bond graphs and genetic programming. This classical inverse problem shares characteristics with many other system synthesis problems, such as electric circuit and controller synthesis, in terms of epistasis and multi-modality of the search space. Critical issues of open-ended topology search by genetic programming are investigated, including encoding, population seeding, scalability and evolvability. For the eigenvalue problems, we have found there exists a correlation between structure and function that is important for efficient topology search. Standard genetic programming has been used to solve up to 20-eigen-value problems, finding the target system of bush topology out of 823,065 possibilities with only 29506 topology evaluations.", notes = "Also known as \cite{1384751}", }

Genetic Programming entries for Jianjun Hu Erik Goodman Ronald C Rosenberg