МОДЕЛИРОВАНИЕ ПРОСТРАНСТВА СТРАТЕГИЙ ЗАДАЧИ «ДИЛЕММА ЗАКЛЮЧЕННОГО»

Abstract

An iterated version of the game "Prisoner's Dilemma" is used as a model of cooperation largely due to the wide range of strategies that the subjects can use. The problem of the effec-tiveness of strategies for solving the Iterated Prisoner's Dilemma (IPD) is most often considered from the point of view of information models, where strategies do not take into account the relationship that arise when real people play. Some of these strategies are obvious, others depend upon social context. In our paper, we use one of the promising directions in the development of studying IPD strategies – the use of artificial neural networks. We use neural networks as a modeling tool and as a part of game environment. The main goal of our work is to build an information model that predicts the behavior of an individual person as well as group of people in the situation of solving of social dilemma. It takes into account social relationship, including those caused by experimental influence, gender differences, and individual differences in the strategy for solving cognitive tasks. The model demonstrates the transition of individual actions into socially determined behavior. Evaluation of the effect of socialization associated with the procedure of the game provides additional information about the effectiveness and characteristics of the experimental impact.The paper defines the minimum unit of analysis of the IPD player's strategy in a group, the identity with which can be considered as a variable. It discusses the influence of the experi-mentally formed group identity on the change of preferred strategies in social dilemmas. We use the possibilities of neural networks as means of categorizing the results of the prisoner's iterative dilemma in terms of the strategy applied by the player, as well as social factors. We define the patterns of changes in the IPD player's strategy before and after socialization are determined. The paper discusses the questions of real player's inclination to use IPD solution strategies in their pure form or to use the same strategy before and after experimental inter-ventions related to social identity formation. It is shown that experimentally induced socialization can be considered as a mechanism for increasing the degree of certainty in the choice of strategies when solving IPD task. It is found out that the models based on neural networks turn out to be more efficient after experi-mentally evoked social identity in a group of 6 people; and the models based on neural net-works are least effective in the case of predicting a subject's belonging to a gender group. When solving IPD problems by real people, it turns out to be possible to talk about generalized strategies that take into account not only the evolutionary properties of «pure» strategies, but also reflect various social factors.