CONSUMER BEHAVIOUR MODELLING WITH APPLIANCE OF ARTIFICIAL NEURAL NETWORKS
The main goal of the described research is developing a model of consumer’s behavior in conditions of making a long-term choice having some external and internal limitations. For consumer’s behavior modelling in such conditions, except for mathematical models of decision-making based on the theory of John von Neumann and O. Mogrenstern, an artificial neural network approach has been applied. The report describes the first of the series of experiments, developed and partially conducted in “Dubna” state university in order to test the hypothesis about the type of decision-making algorithm. The result of the first experiment has been negative, which lead to correction of the second experiment conditions and to refinement of the expected type of decision-making algorithm. The final choice of respondents (output, y ) together with some parameters of choice supplied to respondents (inputs, such as: an expected effect for each of possible decisions, x<sub>1</sub> ; probability for this effect appearance, x<sub>2</sub> ; its time remoteness from the decision making moment, x<sub>3</sub> ) were used as a learning selection for the artificial neural network at analytical platform DataBase Deductor Studio Academic 5.3. The main goal of the experiment is to test the hypothesis about existence of attributive version of von Neumann and Mogrenstern decision making model, where input data described to an agent not using some sharp cardinal measures (such as expected result and its probability), but using some subjectively percepted attributive measures, described above. One of the proposed algorithms has been confirmed after being processed with applying of neural network. Economical agent’s behavior modelling using the described method must give an application of software product, being able to imitate behavior of economical agents in some commons market and everyday life situations.