A Multi-Agent Context-Management System for RECON Intelligence Analysis

  • Alexis Morris
  • William Ross
  • Mihaela Ulieru


Adaptive systems require technologies to enable high synchronicity between its users and their unfolding situation dynamics, in concert with system response actions. To be effective, a multi-dimensional view of context must be considered and incorporated. This work advances the development of such a system for RECON, an initiative to support intelligence analysts with a novel context-management and case-based recommendation capability. The central concepts involved in the management of explicit and implicit contexts are presented and are developed into a novel multi-agent approach. In particular a new context-sensitive cognitive model and a community of expert service-oriented agents are proposed to facilitate and improve system adaptations to user-specific, situational, and system states. These designs pave the way towards future developments and experiments in improving human–machine interaction with adaptive context-management systems.



This work was funded in part by Defence R&D Canada, Thales Research and Technology Canada, and a research partnership grant from the Department of National Defence and the Natural Sciences and Engineering Research Council of Canada.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Faculty of Computer ScienceUniversity of New BrunswickFrederictonCanada
  2. 2.School of Information TechnologyCarleton UniversityOttawaCanada

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