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

doi:10.1016/j.procs.2015.03.005

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

Engineering Division (Great Valley)

Research output: Contribution to journal › Conference article › peer-review

28 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.

Original language	English (US)
Pages (from-to)	76-85
Number of pages	10
Journal	Procedia Computer Science
Volume	44
Issue number	C
DOIs	https://doi.org/10.1016/j.procs.2015.03.005
State	Published - 2015
Event	18th Conference on Plasma-Surface Interactions, PSI 2015, 5-6 February 2015, Moscow, Russian Federation and the 1st Conference on Plasma and Laser Research and Technologies, PLRT 2015, 18-20 February 2015, Moscow, Russian Federation - Sankt Augustin, Germany Duration: Jun 7 2013 → …

All Science Journal Classification (ASJC) codes

Computer Science(all)

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10.1016/j.procs.2015.03.005

Cite this

@article{f5db739d9e004bfa8694bdd5eb10a235,

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

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.",

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

note = "Funding Information: This material is based upon work supported, in whole or in part, by the U.S. Department of Defense, through the Systems Engineering Research Center (SERC), under Contract H98230-08-D-0171. The SERC is a federally funded University Affiliated Research Center managed by Stevens Institute of Technology. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the United States Department of Defense. Publisher Copyright: {\textcopyright} 2015 Published by Elsevier B.V.; 18th Conference on Plasma-Surface Interactions, PSI 2015, 5-6 February 2015, Moscow, Russian Federation and the 1st Conference on Plasma and Laser Research and Technologies, PLRT 2015, 18-20 February 2015, Moscow, Russian Federation ; Conference date: 07-06-2013",

year = "2015",

doi = "10.1016/j.procs.2015.03.005",

language = "English (US)",

volume = "44",

pages = "76--85",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier BV",

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Flexible and intelligent learning architectures for SoS (FILA-SoS) : Architectural evolution in systems-of-systems. / Agarwal, Siddhartha; Pape, Louis E.; Dagli, Cihan H.; Ergin, Nil K.; Enke, David; Gosavi, Abhijit; Qin, Ruwen; Konur, Dincer; Wang, Renzhong; Gottapu, Ram Deepak.

In: Procedia Computer Science, Vol. 44, No. C, 2015, p. 76-85.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Flexible and intelligent learning architectures for SoS (FILA-SoS)

T2 - 18th Conference on Plasma-Surface Interactions, PSI 2015, 5-6 February 2015, Moscow, Russian Federation and the 1st Conference on Plasma and Laser Research and Technologies, PLRT 2015, 18-20 February 2015, Moscow, Russian Federation

AU - Agarwal, Siddhartha

AU - Pape, Louis E.

AU - Dagli, Cihan H.

AU - Ergin, Nil K.

AU - Enke, David

AU - Gosavi, Abhijit

AU - Qin, Ruwen

AU - Konur, Dincer

AU - Wang, Renzhong

AU - Gottapu, Ram Deepak

N1 - Funding Information: This material is based upon work supported, in whole or in part, by the U.S. Department of Defense, through the Systems Engineering Research Center (SERC), under Contract H98230-08-D-0171. The SERC is a federally funded University Affiliated Research Center managed by Stevens Institute of Technology. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the United States Department of Defense. Publisher Copyright: © 2015 Published by Elsevier B.V.

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

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JO - Procedia Computer Science

JF - Procedia Computer Science

SN - 1877-0509

IS - C

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ER -

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

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