Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Population is the fundamental basis of any evolution (Novak, 2006). This statement is true both in biological and artificial evolutionary systems. Population dynamics studies short and long-term changes of the certain population features, and is a branch of life sciences. Here,  discuss new properties of population of binary chromosomes evolved by genetic algorithm (GA), which is one of the possible implementations of artificial evolutionary systems. In particular,  introduce a theorem (Theorem 3) allowing us to determine the minimal number of simple operations necessary to restore the entire space to explore. The work is partly based on Pliszka and Unold (2011, 2012). The discipline of GAs (and broadly Evolutionary Computation EC) is still focused more on the empirical aspects of algorithms than theoretical studies. Methods, which are currently in use in theoretical studies of these algorithms, could be classified into one of the following groups: schema theory, Markov chains theory, dimensional analysis, order statistics, quantitative genetics, orthogonal functions analysis, quadratical dynamical systems, and statistical physics. Simplistic assumptions have frequently been adopted in the theoretical analyses and these have deformed the analyzed algorithms in such a way that they question the real connection beten the results obtained and the investigated algorithms. The essential step in GA/EC is to determine the representation of computational population (Hu and Banzhaf, 2010). Another one is to define the method of gene duplication. Most of GAs use linear binary representations, and the most standard one is an array of bits. Due to fixed size of such representations, their parts are easily aligned. This facilitates simple crossover operation.
['Z Pliszka', 'Olgierd Unold']
I am writing a research paper on a idea Some Remarks on Dynamics of Binary Chromosomes Population
[{"from": "human", "value": "I am writing a research paper on a idea Some Remarks on Dynamics of Binary Chromosomes Population"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Population is the fundamental basis of any evolution (Novak, 2006). This statement is true both in biological and artificial evolutionary systems. Population dynamics studies short and long-term changes of the certain population features, and is a branch of life sciences. Here,  discuss new properties of population of binary chromosomes evolved by genetic algorithm (GA), which is one of the possible implementations of artificial evolutionary systems. In particular,  introduce a theorem (Theorem 3) allowing us to determine the minimal number of simple operations necessary to restore the entire space to explore. The work is partly based on Pliszka and Unold (2011, 2012). The discipline of GAs (and broadly Evolutionary Computation EC) is still focused more on the empirical aspects of algorithms than theoretical studies. Methods, which are currently in use in theoretical studies of these algorithms, could be classified into one of the following groups: schema theory, Markov chains theory, dimensional analysis, order statistics, quantitative genetics, orthogonal functions analysis, quadratical dynamical systems, and statistical physics. Simplistic assumptions have frequently been adopted in the theoretical analyses and these have deformed the analyzed algorithms in such a way that they question the real connection beten the results obtained and the investigated algorithms. The essential step in GA/EC is to determine the representation of computational population (Hu and Banzhaf, 2010). Another one is to define the method of gene duplication. Most of GAs use linear binary representations, and the most standard one is an array of bits. Due to fixed size of such representations, their parts are easily aligned. This facilitates simple crossover operation."}]