Maritime Domain Awareness via Agent Learning and Collaboration

Abstract

Maritime security is vital to US security. Enhanced Maritime Domain Awareness (MDA) of potential threats in this dynamic environment can be achieved, yet requires integrated analysis from numerous sources in real time. We will present a learning agent technology that integrates structured and unstructured data and discovers behavior patterns from varied sources such as: Automatic Information Systems (AIS), Coast Guard, and police contextual information including: maritime commercial activities, weather, terrain, environmental conditions, maritime incidents, casualties, and military exercises. These discovered patterns can help correlate warnings and reduce false alarms in support of maritime security. We will show our test results from the Trident Warrior (TW08) exercise.