A note on a quantitative genetic approach for modelling of differentiation tasks

Learning capacities and cognitive abilities of farm animals will become more important and they will have an impact on animal welfare and productivity. Scientific examinations of these aspects presuppose genetic models. This paper presents an approach for modelling differentiation tasks in animal learning on a quantitative genetic basis. The approach links the likelihood function, to make a correct decision, with the two-dimensional density function, capable to be to decide right. The proposed model is able to depict several situations in learning processes of populations. Its parameters characterize the theoretical course of the learning process and also the stage of learning which a population has reached. The approach can be used to estimate parameters of a learning process and of the genetic disposition to learn, to estimate breeding values of learning capacity and to fit models on population's learning capability under selection.