Modelling insurgent and terrorist networks as self-organised complex adaptive systems

摘要

This paper introduces a multi-agent-based simulation toolkit (called SOTCAC) that uses autonomous, intelligent agents to represent the components of coevolving terrorist network (TNet) and counterterrorist network (CTNet). The model (currently in development) is predicated on the proposition that adaptive agents can be used to describe the self-organised, emergent behaviour of TNets - conceived as complex adaptive systems - on three interrelated dynamical levels: (1) dynamics on networks, in which notional terrorist agents process and interpret information, search and acquire resources and adapt to other agents' actions; (2) dynamics of networks, in which the TNet itself is a fully dynamic, adaptive entity and whose agents build, maintain and modify the network's local (and therefore, collectively, its global) topology and (3) dynamics between networks, in which the TNet and CTNet mutually coevolve. The TNet's 'goal' is to achieve the critical infrastructure (of manpower, weapons, financial resources and logistics) required to strike, while the CTNet's mission is to prevent the TNet from doing so. The ultimate goal for developing SOTCAC is to provide INTEL analysts with a larger context of 'plausibly possible' TNet«-» CTNet coevolutions - as they could be - so that TNets can be better understood as they are and as they are likely to adapt. And since the way in which the CTNet collects, assimilates, fuses and derives inferences about what the terrorist 'looks like' is prescribed (via local, context-dependent properties and behaviours) - not scripted - SOTCAC may also help analysts discover novel data-fusion and 'ground truth' inference strategies.