How information and communication technologies change trends in modelling political processes: towards an agent-based approach

Abstract

The development of information and communication technologies and computing power leads to the emergence of additional opportunities for modeling political processes. In the past decades, mathematical models have been developed mainly in a game-theoretic setting; today we witness an expanding stream of research applying agent-based (multi-agent) approach. This trend is quite natural. There have been changes in political participation and in the forms of collective interaction of individuals and groups, induced by digital technologies. Researchers have developed theoretical approaches to political participation, focusing on the network interaction and implementing the “bottom-up” logic that infers the macro-properties of the system from the characteristics and interactions of individual agents. Thus, the theoretical foundations for an agent-based modeling, most promising in its network version, have been developed. This approach, however, required a more complex description of the individual motivation and decision making in comparison to the dominant game-theoretic paradigm. One of the key points is that motivation is considered to be linked to the network position of agents, since the individual is guided by the actions of her neighbors. Thus, the course of the political process is determined not only by the properties and decisions of its participants, but also by the type of network architecture that connects them. Within this research framework, a computational experiment, assuming a controlled variation of parameters, plays a special role. Two main strategies of such an experiment are considered: the grid search and the Monte Carlo method. The prospects of agentbased modeling in its network form are related to the study of the dynamical political processes, taking into account the structures of trust and social capital, as well as the resources and mechanisms of collective action.