Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Natural Computing
Erschienen in: Natural Computing 1/2011

01.03.2011

Grammar-based immune programming

verfasst von: Heder S. Bernardino, Helio J. C. Barbosa

Erschienen in: Natural Computing | Ausgabe 1/2011

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper describes Grammar-based Immune Programming (GIP) for evolving programs in an arbitrary language by immunological inspiration. GIP is based on Grammatical Evolution (GE) in which a grammar is used to define a language and decode candidate solutions to a valid representation (program). However, by default, GE uses a Genetic Algorithm in the search process while GIP uses an artificial immune system. Some modifications are needed of an immune algorithm to use a grammar in order to efficiently decode antibodies into programs. Experiments are performed to analyze algorithm behavior over different aspects and compare it with GEVA, a well known GE implementation. The methods are applied to identify a causal model (an ordinary differential equation) from an observed data set, to symbolically regress an iterated function f(f(x)) = g(x), and to find a symbolic representation of a discontinuous function.
Vorheriger Artikel An immune-inspired approach to qualitative system identification of biological pathways
Nächster Artikel Priming: making the reaction to intrusion or fault predictable

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Fußnoten
2
Kleene star is a unary operation widely used for regular expressions in which if N is a set of symbols or characters, then N * is the set of all strings composed by symbols in N, including the empty string.
 
Literatur
Amarteifio S, O’Neill M (2005) Coevolving antibodies with a rich representation of grammatical evolution. In: Corne D, Michalewicz Z, Dorigo M, Eiben G, Fogel D, Fonseca C, Greenwood G, Chen TK, Raidl G, Zalzala A, Lucas S, Paechter B, Willies J, Guervos JJM, Eberbach E, McKay B, Channon A, Tiwari A, Volkert LG, Ashlock D, Schoenauer M (eds) Proceedings of the 2005 IEEE Congress on Evolutionary Computation, IEEE Press, Edinburgh, UK, vol 1, pp 904–911
Bernardino HS, Barbosa HJ (2009a) Grammar-based immune programming for symbolic regression. In: Proceedings of the 2009 International Conference on Artificial Immune Systems, LNCS 5666, Springer, Berlin Heidelberg, pp 274–287
Bernardino HS, Barbosa HJ (2009b) Nature-inspired algorithms for optimisation. Springer, Berlin Heidelberg, chap Artificial Immune Systems for Optimization, pp 389–411
Bielecki A, Strug B (2005) An evolutionary algorithm for solving the inverse problem for iterated function systems for a two dimensional image. In: Proceedings of the 4th International Conference on Computer Recognition Systems CORES 05, Springer, Berlin Heidelberg, pp 347–354
Burnet FM (1959) The clonal selection theory of acquired immunity. Cambridge University Press, Cambridge
de Castro LN, Timmis J (2002) An artificial immune network for multimodal function optimization. In: Proc. of the 2002 IEEE World Congress on Computational Intelligence, Honolulu, Hawaii, USA, vol I, pp 669–674
de Castro LN, von Zuben FJ (2002) Learning and optimization using the clonal selection principle. IEEE Trans Evo Comp 6(3):239–251CrossRef
Chomsky N (2002) Syntactic structures. Mouton de Gruyter, Berlin, New YorkCrossRef
Ciccazzo A, Conca P, Nicosia G, Stracquadanio G (2008) An advanced clonal selection algorithm with ad-hoc network-based hypermutation operators for synthesis of topology and sizing of analog electrical circuits. In: Bentley PJ, Lee D, Jung S (eds) Proceedings of the international conference on artificial immune systems—ICARIS 2008, Springer, LNCS, vol 5132, pp 60–70
Cramer NL (1985) A representation for the adaptive generation of simple sequential programs. In: Proceedings of the 1st international conference on genetic algorithms, L. Erlbaum Associates Inc., Hillsdale, NJ, USA, pp 183–187
Cutello V, Narzisi G, Nicosia G, Pavone M (2005) Clonal selection algorithms: a comparative case study using effective mutation potentials. In: Proceedings of the international conference on artificial immune systems—ICARIS 2005, Springer, LNCS, vol 3627, pp 13–28
Dasgupta D, Nino F (2008) Immunological computation: theory and applications. Auerbach Publications, Boston, MA, USACrossRef
Elseth GD, Baumgardner KD (1995) Principles of modern genetics. Brooks Cole, Pacific Grove, CA
Ferreira C (2001) Gene expression programming: a new adaptive algorithm for solving problems. ArXiv Computer Science e-prints arXiv:cs/0102027
Gan Z, Chow TW, Chau W (2009a) Clone selection programming and its application to symbolic regression. Expert Syst Appl 36(2):3996–4005CrossRef
Gan Z, Zhao MB, Chow TW (2009b) Induction machine fault detection using clone selection programming. Exp Syst Appl 36(4):8000–8012CrossRef
Johnson CG (2003) Artificial immune system programming for symbolic regression. In: Proceedings of the 6th European conference on genetical programming—EuroGP 2003, pp 345–353
Koza JR (1992) Genetic programming: on the programming of computers by means of natural selection (complex adaptive systems). The MIT Press, Cambridge, MA
Koza JR, Bennett III FH, Andre D, Keane MA (2000) Synthesis of topology and sizing of analog electrical circuits by means of genetic programming. Comput Methods Appl Mech Eng 186(2–4):459–482MATHCrossRef
Lau A, Musilek P (2009) Immune programming models of cryptosporidium parvum inactivation by ozone and chlorine dioxide. Inf Sci 179(10):1469–1482CrossRef
McKinney B, Tian D (2008) Grammatical immune system evolution for reverse engineering nonlinear dynamic bayesian models. Cancer Inform 6:433–447
O’Neill M, Brabazon A (2006) Grammatical differential evolution. In: Proceedings of the 2006 international conference on artificial intelligence—ICAI 2006, CSREA Press, Las Vegas, Nevada, USA, pp 231–236
O’Neill M, Ryan C (2001) Grammatical evolution. IEEE Trans Evol Comput 5(4):349–358CrossRef
O’Neill M, Ryan C (2003) Grammatical evolution: evolutionary automatic programming in an arbitrary language. Kluwer Academic Publishers, Boston, MAMATH
O’Neill M, Brabazon A, Adley C (2004) The automatic generation of programs for classification problems with grammatical swarm. In: Congress on evolutionary computation—CEC 2004, vol 1, pp 104–110
Ryan C, Collins J, Neill MO (1998) Grammatical evolution: evolving programs for an arbitrary language. In: LNCS 1391, Proceedings of the first European workshop on genetic programming, Springer-Verlag, pp 83–95
Schmidt MD, Lipson H (2008) Data-mining dynamical systems: automated symbolic system identification for exploratory analysis. In: Proceedings of the Biennial ASME conference on engineering systems design and analysis—ESDA08, Haifa, Israel
Schmidt MD, Lipson H (2009) Solving iterated functions using genetic programming. In: Proceedings of the 11th annual conference companion on genetic and evolutionary computation conference: late breaking papers, ACM, New York, NY, USA, GECCO ’09, pp 2149–2154, doi:10.​1145/​1570256.​1570292
Smith SF (1980) A learning system based on genetic adaptive algorithms. PhD thesis, University of Pittsburgh, Pittsburgh, PA, USA
Smith SF (1983) Flexible learning of problem solving heuristics through adaptive search. In: IJCAI’83: Proceedings of the eighth international joint conference on artificial intelligence, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, pp 422–425
Metadaten
Titel
Grammar-based immune programming
verfasst von
Heder S. Bernardino
Helio J. C. Barbosa
Publikationsdatum
01.03.2011
Verlag
Springer Netherlands
Erschienen in
Natural Computing / Ausgabe 1/2011
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI
https://doi.org/10.1007/s11047-010-9217-x

Weitere Artikel der Ausgabe 1/2011

Natural Computing 1/2011 Zur Ausgabe

OriginalPaper

A simple mass-action model for the eukaryotic heat shock response and its mathematical validation

OriginalPaper

Friction-based sorting

OriginalPaper

Optimization of supply diversity for the self-assembly of simple objects in two and three dimensions

OriginalPaper

A computational modeling for real ecosystems based on P systems

OriginalPaper

P systems with active membranes: trading time for space

OriginalPaper

Towards a neighborhood simplification of tile systems: From Moore to quasi-linear dependencies

Premium Partner

    Bildnachweise