Agent-based modelling has gained popularity as a useful technique for obtaining insights into the behaviour of complex adaptive systems in various fields including economics, sociology and ecology. With its complex interactions between routes, schedules and engagement strategies, transit through piracy-affected waters is a problem very well suited for the application of this powerful modelling approach. Within the AgentC project, we have been developing a data-driven, agent-based model of global maritime traffic explicitly accounting for the effects of maritime piracy. The model employs finite state machines to represent the behaviour of merchant, pirate and naval vessels. It accurately replicates global shipping patterns and approximates real-world distribution of pirate attacks. By conducting and analysing results from thousands of simulation runs, the developed model and related tools allow gaining qualitative and quantitative insights into complex relationships governing piracy risks and costs. Further on, we utilize the simulation to conduct what-if analysis of possible piracy counter-measures and evaluate their effectiveness. Because of their strong application potential, the model and the tools are currently considered by the U.N. International Maritime Organization for potential use in assessing future operational counter-piracy measures, including new transit corridors and extended group transit schemes.
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