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A common distributed intelligent system architecture is Multi Agent Systems (MASs).
Integration of functions within an intelligent system architecture would result in improved plant performance, safety and an increase in production.
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As illustrated in Fig. 2, these systemic strategies include: (1) the creation of regional TBI collaborative networks, (2) the integration of intelligent system architectures, (3) the innovation and virtualization of care, (4) emergency medical leadership, and (5) societal value paradigm shifts.
The communication model is described and implemented using open intelligent information system architecture.
A behavior based, autonomous intelligent control system architecture developed for autonomous underwater vehicles is used to demonstrate the integration.
Additionally, the use of the described patterns in the design of an intelligent tutoring system architecture is exemplified.
To facilitate implementation of the communication model, a conceptual framework for developing module-based knowledge systems called "open intelligent information system architecture" is utilized.
But typical intelligent tutoring system architectures make use of a domain model that provides a limited set of approved solutions to problems presented to students.
The majority of Intelligent Tutoring System architectures are focused on supporting learners through content retrieval or in one or more given subject matters; examples of this can be found in Baghera [1], MyClass, Andes [2], Gramy, Advanced Geometry Tutor [7].
To implement RTS game system on mobile intelligent terminal, the system architecture based on C/S was designed, divided into the cloud subsystem and the mobile terminal subsystem.
This paper proposes a radio frequency identification (RFID -based intelligent decision suppoRFID -basedrchintelligent handecisionuction monitoring and supporting in a disystemted marchitecture environmento
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