Flexible and intelligent learning architectures for SoS (FILA-SoS): Architectural evolution in systems-of-systems

Siddhartha Agarwal, Louis E. Pape, Cihan H. Dagli, Nil K. Ergin, David Enke, Abhijit Gosavi, Ruwen Qin, Dincer Konur, Renzhong Wang, Ram Deepak Gottapu

Research output: Contribution to journalConference articlepeer-review

24 Scopus citations

Abstract

The dynamic planning for a system-of-systems is a challenging endeavor. Department of Defense (DoD) programs constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget, and uncertainty. It is therefore necessary for the DoD to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. The DoD currently is looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This paper gives an overview of a novel methodology known as the Flexible Intelligent & Learning Architectures in System-of-Systems (FILA-SoS). This approach allows for analyzing sequential decisions in evolving SoS architectures. An ISR SoS example illustrates an application of the method.

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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