An Interdisciplinary Research Approach to Political Science - Specific Modeling and Simulation Tools

This paper introduces a research approach on new modeling and simulation techniques for the social and political behavior and attitude in the context of social and political change. Political Science needs specific analysis, representation, modeling, simulation and predictive tools. The need for such techniques is motivated by the increasing complexity of the empirical experimental data and conceptual knowledge involved in the representation, analysis, modeling and prediction of social behavior and attitude with respect to social and political value systems, especially when such values are subject to social change processes. The work reported here aims at developing a more believable approach on artificial agents and artificial societies by means of: (i) new representation and modeling concepts of the artificial agent as an agent-environment interaction system, (ii) new representation and modeling concepts of the interaction and knowledge in artificial agents, and (iii) new computational theory explaining the learning and the emergence mechanisms of social behavior and attitude in an artificial society. The concepts of autonomous agents, agent-environment interaction systems (aeis), and computational attitude are defined and explained. Attitude emergence in artificial society is defined and explained by means of the Theory of Learning. A Case Study on attitude emergence in the simulation of a team cooperation game is described, analyzed and an interpretation of the computational attitude is provided