This paper focuses on the development of a spatial evolutionary multiagent social network for studying the macroscopic-behavioral dynamics of civil violence, as a result of microscopic game-theoretic interactions between goal-oriented agents. Agents are modeled from multidisciplinary perspectives and their strategies are evolved over time via collective coevolution and independent learning. Spatial and temporal simulation results reveal fascinating global emergence phenomena and interesting patterns of group movement and autonomous behavioral development. Extensions of differing complexity are also used to investigate the impact of various decision parameters on the outcome of unrest. Analysis of the results provides new insights into the intricate dynamics of civil upheavals and serves as an avenue to gain a more holistic understanding of the fundamental nature of civil violence.
['Hanyang Quek', 'Kay Chen Tan', 'Hussein A. Abbass']
Evolutionary Game Theoretic Approach for Modeling Civil Violence