Details zur Publikation

Kategorie Textpublikation
Referenztyp Buchkapitel
DOI 10.1007/978-3-540-24653-4_6
Titel (primär) Self-adaptive scouting - Autonomous experimentation for systems biology
Titel (sekundär) Applications of evolutionary computing
Autor Matsumaru, N.; Centler, F.; Zauner, K.P.; Dittrich, P.
Herausgeber Raidl, G.R.; Cagnoni, S.; Branke, J.; Wolfe Corne, D.; Drechsler, R.; Jin, Y.; Johnson, C.G.; Machado, P.; Marchiori, E.; Rothlauf, F.; Smith, G.D.; Squillero, G.
Quelle Lecture Notes in Computer Science
Erscheinungsjahr 2004
Department UMB
Band/Volume 3005
Seite von 52
Seite bis 62
Sprache englisch
Abstract We introduce a new algorithm for autonomous experimentation. This algorithm uses evolution to drive exploration during scientific discovery. Population size and mutation strength are self-adaptive. The only variables remaining to be set are the limits and maximum resolution of the parameters in the experiment. In practice, these are determined by instrumentation. Aside from conducting physical experiments, the algorithm is a valuable tool for investigating simulation models of biological systems. We illustrate the operation of the algorithm on a model of HIV-immune system interaction. Finally, the difference between scouting and optimization is discussed.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=4334
Matsumaru, N., Centler, F., Zauner, K.P., Dittrich, P. (2004):
Self-adaptive scouting - Autonomous experimentation for systems biology
In: Raidl, G.R., Cagnoni, S., Branke, J., Wolfe Corne, D., Drechsler, R., Jin, Y., Johnson, C.G., Machado, P., Marchiori, E., Rothlauf, F., Smith, G.D., Squillero, G. (eds.)
Applications of evolutionary computing
Lect. Notes Comput. Sci. 3005
Springer, Berlin, Heidelberg, New York, p. 52 - 62 10.1007/978-3-540-24653-4_6