We explore how multi-agent systems, a branch of artificial intelligence, can be used to improve maritime security, with particular focus on fighting maritime piracy. Our ultimate objective is to develop an integrated set of algorithmic techniques for maximizing transit security given the limited protection resources available. We achieve this by improving the coordination of the movement of merchant vessels and naval patrols, while taking into account the behavior of pirates.Got that? Well, here's a video:
In order to evaluate the proposed techniques and to gain better insight into the structure and dynamics of maritime piracy, we also employ agent-based simulation and machine learning techniques to build dynamic models of maritime transit and to model and assess piracy risk.
All methods are implemented within a modular software testbed featuring a scalable simulation engine, connectors to real-world data sources and powerful visualization front-end based on Google Earth.
UPDATE: Nice visual of sea lanes, a thwarted pirate attack and more. Suggest using full screen mode. Setting of optimal patrol sectors on transit lane is interesting.
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