Title :
Complexity theory and genetics
Author_Institution :
Math. Inst., Czechoslovak Acad. of Sci., Prague, Czechoslovakia
fDate :
28 Jun- 1 Jul 1994
Abstract :
We introduce a population genetics model in which the operators are effectively computable-computable in polynomial time on probabilistic Turing machines. We shall show that in this model a population can encode easily large amount of information from environment into genetic code. Then it can process the information as a parallel computer. More precisely, we show that it can stimulate polynomial space computations in polynomially many steps, even if the recombination rules are very simple
Keywords :
Turing machines; biocybernetics; cellular biophysics; computational complexity; parallel algorithms; stochastic automata; complexity theory; genetics; parallel computer; polynomial space computations; polynomial time; population genetics model; probabilistic Turing machines; recombination rules; Complexity theory; Computational complexity; Computational modeling; Concurrent computing; Frequency; Genetic mutations; Mathematical model; Organisms; Polynomials; Turing machines;
Conference_Titel :
Structure in Complexity Theory Conference, 1994., Proceedings of the Ninth Annual
Conference_Location :
Amsterdam
Print_ISBN :
0-8186-5670-0
DOI :
10.1109/SCT.1994.315787
