Exploring Factors and Policies for Poverty by Agent-based Simulation

This paper presents a case study on agent-based simulation concerning the growth of poverty. The aim is to support policy makers and researchers to explore different factors concerning specific localities and policies that affect poverty's nature and growth. The paper presents a rather inclusive model, incorporating characteristics about the local environment, the local economic structure, community institutions and demographic characteristics, together with characteristics of individuals populating the locality. Experimental results show the potential of the constructed model. We also discuss various visualization strategies that will support decision makers to better explore the complexity of the phenomenon and the effectiveness of foreseen policies.