Use of agent-based modeling to model intermediate force capabilities in (counter)mobility crowd scenarios

Abstract

In this paper, we use an agent-based model (ABM) to run (counter)mobility scenarios to explore which characteristics of intermediate force capabilities (IFC) are relevant to these, and how they can affect outcomes in gray zone conflicts. Using an ABM called Map-Aware Non-Uniform Automata (MANA), developed by the New Zealand Defense Technology Agency, we implemented two scenarios where the friendly forces’ mobility was limited by large groups of civilians. Then, we employed data farming and analytics methods to analyze the data and identify key parameters influencing the outcomes. The main parameters appeared to be the IFC Range, Power (a measure of the duration of the effect), and Crowd Density. Future research could include a wide range of mobility scenarios and possibly a more detailed IFC representation.

An Analysis of Multi Agent Systems Agent Based Programming

“…It is notable for being the initial integrated software that provides a simple approach to depicting the actions of agents that change in response to groundwater conditions. A comprehensive examination of agent-based modeling and simulation (ABMS) tools and applications is available in [40]. In [41], a comprehensive methodological guide is presented for utilizing BDI agents within a social simulation.…”