Political Science: Artificial Intelligence Applications

Abstract

Scholars who apply artificial mtelligence to political questions seek, most generally, to expand the scope and relevance of political model analysis. By incorporating the effects of variable human notions, traditions, and meanings, they seek to humanize political models. Most early applications of artificial intelligence in political science research address substantive issues pertaining to political decision making. Most of these works apply production-system technology to construct choice models in for eign-policy decision contexts. In recent years, political applications have begun to diver sify. Today, lively research efforts flourish in widely varied application areas, such as computational text analysis, logic programming, computer learning, and conflict sim ulation. The works reviewed here constitute the early steps of a nascent program of study. Much remains to be accomplished. Nevertheless, the efforts conducted thus far suggest many potentially fruitful research avenues. Keywords: artificial intelligence, production systems, logic programming, computational hermeneutics, belief models, political simulation, political science.

Big Questions of Artificial Intelligence (AI) in Public Administration and Policy

“…Similarly, Shangraw (1987) argued that expert systems are an opportunity to operationalize the public policymaking strategy. Duffy and Tucker (1995) examined the use of AI from a political science perspective and argued that traditions and meanings could be challenging in modelling AI for political problems. However, scholars emphasized that machine learning systems, election simulations, and expert systems can often be used in future policy modelling.…”

Computational Politics and Economy for the Establishment of an Integrated Intelligent Government

“…They apply machine learning techniques for discovering knowledge in international conflicts and conflict management databases. G. Duffy and S. A. Tucker [7] focus on the application of AI in political science; they explain many intelligent models such as "American decision-making during the Cuban missile crisis", "Military expenditures decision making", and etc. Edith and Lane A. Hemaspaandra [8] investigate computation-related results in the study of electoral systems in respect to determining the winner.…”

Computational Conflict Research

“…, following a complex systems approach, developed a discrete model composed of states arrayed geographically and with imperfect perception, provided each with a quantity of "power," endowed each with action rules based on realistic principles, and set them off to interact with one another in iterative cycles of conflict and cooperation. This model aimed to investigate the likelihood that a power equilibrium can be achieved under particular conditions (Duffy and Tucker, 1995). Cusack and Stool (1990) extended the Bremer and Mihalka model incorporating more realistic rules in which states play multiple roles and they assessed the effects that different sets of rules have on the survival and endurance of states and state systems (Duffy and Tucker, 1995).…”