fuzzy logics of living organisms
Living organisms or biosystems can be represented as super-complex systems
with dynamics that is not reducible to that of their components, such as molecules and atoms. It is an empirically accepted fact that living organisms exhibit a wide degree of `biological variability': genetic, epigenetic and also phenotypic, metabolic within the same species; their behavior and dynamics thus exhibit a type of `fuzziness' (refs.[2,3]) that unlike Zadeh's fuzzy sets characteristic ([7,8]) is neither random nor always following a (symmetric) Gaussian distribution.
It has been proposed that the operational logics underlying super-complex systems dynamics
are
many-valued logics
for both genetic and neural networks (refs. [3,6]).
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- 1
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Georgescu, G. 2006, N-valued Logics and Łukasiewicz-Moisil
Algebras, Axiomathes, 16 (1-2): 123-136.
- 2
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Baianu, I.C. and M. Marinescu: 1968, Organismic Supercategories:
Towards a Unitary Theory of Systems. Bulletin of Mathematical Biophysics 30, 148-159.
- 3
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Baianu, I.C.: 1977, A Logical Model of Genetic Activities in Łukasiewicz Algebras: The Non-linear Theory. Bulletin of Mathematical Biology, 39: 249-258.
- 4
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Baianu, I. C.: 1986-1987a, Computer Models and Automata Theory in Biology and Medicine., in M. Witten (ed.),
Mathematical Models in Medicine, vol. 7., Ch.11 Pergamon Press, New York, 1513 -1577; URLs:
CERN Preprint No. EXT-2004-072
,
and html Abstract.
- 5
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Baianu, I. C.: 1987b, Molecular Models of Genetic and Organismic Structures, in Proceed. Relational Biology Symp.
Argentina;
CERN Preprint No.EXT-2004-067
.
- 6
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Baianu, I.C.: 2004. Łukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models (2004). Eprint: w. Cogprints at Sussex Univ.
- 7
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Zadeh, L.A., Fuzzy Sets, Information and Control, 8 (1965) 338ÃÂ-353.
- 8
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Zadeh L. A., The concept of a linguistic variable and its application to approximate reasoning I, II, III, Information Sciences, vol. 8, 9(1975), pp. 199-275, 301-357, 43-80.
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