Intelligent Integration of Human Cognition into the Fused Reasoning Process

The goal of this Phase I effort is foster human interaction with automated systems via a collaborative learning environment to benefit from the collective and dynamic knowledge of a team of experienced analysts. This will be accomplished by applying proven commercial collaborative learning technologies to the challenge of adapting and defeating the ever-changing tactics of today’s adversaries. Collaborative techniques, such as collaborative filtering, have been successfully implemented in dynamic commercial environments with impressive results. For example, Amazon.com has implemented its own unique collaborative filtering algorithm which is responsible for an amazing 35% of its sales as a result of recommendations from other customers with similar preferences and experiences. With today’s systems moving towards a Service Oriented Architecture, it will be possible to continuously communicate in real-time with a population of analysts that can provide valuable and timely feedback to allow an automated system to adapt itself to a constantly changing environment This effort will apply collaborative techniques to the challenge of Smart Data Association (SDA) using multi-INT sources which will allow the development of new Motion Pattern Analysis (MPA) techniques that will automatically detect and recognize both the known and evolving patterns of the dynamic adversary.