Abstract
In this paper we outline a model which incorporates developmental processes into an evolutionary framework. The model consists of three sectors describing development, genetics, and the selective environment. The formulation of models governing each sector uses dynamical grammars to describe processes in which state variables evolve in a quantitative fashion, and the number and type of participating biological entities can change. This program has previously been elaborated for development. Its extension to the other sectors of the model is discussed here and forms the basis for further approximations. A specific implementation of these ideas is described for an idealized model of the evolution of a multicellular organism. While this model does not describe an actual biological system, it illustrates the interplay of development and evolution. Preliminary results of numerical simulations of this idealized model are presented.
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Buss, L. W. (1987). The Evolution of Individuality. Princeton University Press, Princeton, New Jersey. See pp. 31, 69, 98–115.
Fleischer, K. and Barr, A. H. (1993). A simulation testbed for the study of multicellular development: The multiple mechanisms of morphogenesis. In Artificial Life III. Addison-Wesley, 389–416 C. Langton (Ed.).
Gardiner, C. W. (1983). Handbook of Stochastic Methods for Physics, Chemistry, and the Natural Sciences. Springer Verlag, Berlin.
Hopfield, J. J. (1984). Neurons with graded response have collective computational properties like those of two-state neurons. Proceedings of the National Academy of Sciences USA, vol. 81:3088–3092.
Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220:671–680.
Lam, J. and Delosme, J.-M. (1988a). An efficient simulated annealing schedule: derivation. Technical Report 8816, Yale Electrical Engineering Department, New Haven, CT.
Lam, J. and Delosme, J.-M. (1988b). An efficient simulated annealing schedule: implementation and evaluation. Technical Report 8817, Yale Electrical Engineering Department, New Haven, CT.
Lindenmayer, A. (1968). Mathematical models for cellular interaction in development, parts i and ii. Journal of Theoretical Biology, 18:280–315.
Metropolis, N., Rosenbluth, A., Rosenbluth, M. N., Teller, A., and Teller, E. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21:1087–1092.
Mjolsness, E., Sharp, D. H., and Reinitz, J. (1991). A connectionist model of development. Journal of Theoretical Biology, 152:429–453.
Prusinkiewicz, P., Hammel, M. S., and Mjolsness, E. (1993). Animation of plant development. In SIGGRAPH 93 Conference Proceedings. Association for Computing Machinery Press.
Reinitz, J., Mjolsness, E., and Sharp, D. H. (1994). Cooperative control of positional information in Drosophila by bicoid and maternal hunchback. Submitted to J. theor Biol..
Smith, J. M. (1982). Evolution and the Theory of Games. Cambridge University Press, Cambridge.
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© 1995 Springer-Verlag Berlin Heidelberg
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Mjolsness, E., Garrett, C.D., Reinitz, J., Sharp, D.H. (1995). Modeling the connection between development and evolution: Preliminary report. In: Banzhaf, W., Eeckman, F.H. (eds) Evolution and Biocomputation. Lecture Notes in Computer Science, vol 899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59046-3_7
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DOI: https://doi.org/10.1007/3-540-59046-3_7
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