Artificial chemistry - a new metaphor for evolutionary algorithms

  • Vladimír Kvasnička


An artificial chemistry is a branch of contemporary computer science that uses a chemical metaphor as a new highly parallel approach to computations. It can be defined by (1) a set of objects (a chemostat composed of molecules) and (2) a set of transformation rules (chemical reactions), which specify how the objects are transformed into other objects. The purpose of the present short communication is to use the well-known Eigen’s chemical system of replicators as a new (chemical) metaphor. It is then applied in design of the so-called replicator algorithm. This algorithm has some common features with genetic algorithms, but as an advantage of the presented replicator algorithm we consider an existence of relatively simple proof that the algorithm offers globally optimal solutions.


Simulated Annealing Turing Machine Binary String Artificial Life Nondiagonal Element 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Adleman L.M. (1994) Molecular Computation of Solutions of Combinatorial Problems. Science 266, 1021CrossRefGoogle Scholar
  2. 2.
    Banzhaf W., Dittrich P., Eller B. (1999) Topological Interactions in a Binary String System. Physica D 125, 85CrossRefGoogle Scholar
  3. 3.
    Beaver D. (1995) Universal Molecular Computer, unpublished manuscript, available at Scholar
  4. 4.
    Benatre J.-P., Le Metayer D. (1990) The Gamma Model and its Discipline of Programming. Sci. Compo Progr. 15, 55.CrossRefGoogle Scholar
  5. 5.
    Berry G., Boudol G. (1992) The Chemical Abstract Machine. Theoret. Compo Sci. 96, 217MathSciNetMATHCrossRefGoogle Scholar
  6. 6.
    Černý 1. (1985) Thermodynamical Approach to the Traveling Salesman Problem: An Efficient Simulation Algorithm. J Opt. Theory Appl. 45, 41MATHCrossRefGoogle Scholar
  7. 7.
    Dittrich P. (1999) Artificial Chemistries (tutorial material). A tutorial held at ECAL’99, 13–17 September 1999, Lausanne, Switzerland, available at pub/vlado/Artificial_ChemistrylDittrich_tutoriaiAChemECAL99.pdf.Google Scholar
  8. 8.
    Eigen M. (1971) Self organization of matter and the evolution of biological macro molecules. Naturwissenshaften 58, 465CrossRefGoogle Scholar
  9. 9.
    Eigen M., Schuster P. (1977) The Hypercyc1es: A Principle of Natural Evolution. Naturwissenschanften 64, 541; 65, 7; 65, 341CrossRefGoogle Scholar
  10. 10.
    Fogel D. B. (1995) Evolutionary Computation. IEEE Press, New YorkGoogle Scholar
  11. 11.
    Fontana W. (1991) Algorithmic Chemistry. In: Langton C.G. (ed.) Artificial Life II Addison Wesley, Reading, MA, p. 159Google Scholar
  12. 12.
    Haken H. (1979) Pattern Formation and Pattern Recognition — An Attempt to a Synthesis. In: Haken H. (ed.) Pattern Formation by Dynamical Systems and Pattern Recognition. Springer Verlag, HeidelbergCrossRefGoogle Scholar
  13. 13.
    Hjelmfelt A., Weinberg E.D., Ross J. (1991) Chemical Implementation of Neural Networks and Turing Machines. Proc. Natl. Acad Sci. USA 88, 10983MATHGoogle Scholar
  14. 14.
    Jones B.L., Enns R.H., Rangnekar S.S. (1976) On the theory of selection of coupled macromolecular systems. Bulletin of Mathematical Biology 38, 15MATHGoogle Scholar
  15. 15.
    Kauffman S.A. (1993) The Origins of Order: Self-Organization and Selection in Evolution. Oxford University Press, New YorkGoogle Scholar
  16. 16.
    Kirkpatrick S., Gelatt Jr. C.D., Vecchi M.P. (1983) Optimization by Simulated Annealing. Science 220, 671MathSciNetMATHCrossRefGoogle Scholar
  17. 17.
    Kvasnička Y., Pospichal J. (2001) Autoreplicators and Hypercycles in Typogenetics, Journal of Molecular Structure (Theochem) 547, 119CrossRefGoogle Scholar
  18. 18.
    Lipton R.J. (1995) Speeding up Computation via Molecular Biology, unpublished manuscript, available at Scholar
  19. 19.
    Mayoh B. (1995) Biological Computation is Universal. Unpublished manuscript, available at computing/biocomputationNat. psGoogle Scholar
  20. 20.
    Otten R.H.J.M., van Ginneken L.P.P.P. (1989) Annealing Algorithm. Kluwer, BostonCrossRefGoogle Scholar
  21. 21.
    Rothemund P.W.K. (1995) A DNA and Restriction Enzyme Implementation of Turing Machines, unpublished manuscript, available at vlado/Rothemund_dimacs.psGoogle Scholar
  22. 22.
    van Laarhoven P.J.M., and Aarts E.H.L. (1987) Simulated Annealing. Theory and Applications. Reidel, DordrechtMATHGoogle Scholar
  23. 23.
    Voigt H.-M. (1989) Evolution and Optimization: An Introduction to Solving Complex Problems by Replicator Networks. Akademie-Verlag, BerlinMATHGoogle Scholar

Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  • Vladimír Kvasnička
    • 1
  1. 1.Department of MathematicsSlovak Technical UniversityBratislavaSlovakia

Personalised recommendations