Model of interaction between learning and evolution. Computer simulation and analytical results

The current work develops the previous model of interaction between learning and evolution (Red’ko, 2017). The previous model investigated this interaction by means of computer simulation. The mechanisms of the main properties of the interaction between learning and evolution (the genetic assimilation, the hiding effect, the influence of the learning load on the interaction between learning and evolution) were analyzed. The results were obtained for the finite size of the population. Fortunately, there is the possibility to analyze the same effect analytically for the case of the infinite size of the population. The current article considers sufficiently large sizes of population. Computer simulation demonstrates that the essential results of the model do not depend on the population size if this size is sufficiently large. Moreover, at such large population size, the results of computer simulation actually coincide with the results of analytical estimations. We consider the processes of learning and evolution for the population of modeled organisms that have genotype and genotype. Genotypes are modified during evolution, phenotypes are optimized by means of learning. At the end of the generation, organisms are selected in accordance with their final phenotype. The main attention is paid to the hiding effect. This effect means that learning can suppress the evolutionary optimization of genotypes: the optimal phenotype can be found by means of learning for a rather large set of different genotypes, so there is no need to find the optimal genotype. The hiding effect is analyzed by both computer simulation and analytically.