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 contextmanagement 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.

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Morris, A. (Alexis), Ross, W. (William), & Ulieru, M. (2016). A multi-agent context-management system for recon intelligence analysis. doi:10.1007/978-3-319-22527-2_7