Publication Details

Category Text Publication
Reference Category Book chapters
DOI 10.1007/978-3-540-24653-4_6
Title (Primary) Self-adaptive scouting - Autonomous experimentation for systems biology
Title (Secondary) Applications of evolutionary computing
Author Matsumaru, N.; Centler, F.; Zauner, K.P.; Dittrich, P.
Publisher 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.
Source Titel Lecture Notes in Computer Science
Year 2004
Department UMB
Volume 3005
Page From 52
Page To 62
Language 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.
Persistent UFZ Identifier 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