Understanding System of Systems Development Using an Agent- Based Wave Model

Acheson, Paulette; Pape, Louis; Dağli, Ci̇han H.; Kilicay‐Ergin, Nil; Columbi, John; Haris, Khaled

doi:10.1016/j.procs.2012.09.024

Cited by 26 publications

(15 citation statements)

References 10 publications

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“…Tan et al [25] proposed a multiobjective evolutionary algorithm (EA) to obtain system development plans informing which system components should be advanced to which maturity levels within resource limit. Acheson et al [26] used genetic algorithm (GA) to populate initial SoS meta-architecture and formulate the trade space of possible architectures in a "wave model" driven agent-based simulation of SoS evolution. Some of the methods such as ROA, EEA, and TDNs are intuitive to understand, but suffer from the computational complexity when the problem size increases; while others such as EA and GA are not quite intuitive for decision makers to understand in the SoS context and cannot capture the impact of decisions on parameters in the future.…”

Section: System-of-systems Evolutionmentioning

confidence: 99%

Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution

2020

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System of Systems (SoS) is designed to deliver value to participant stakeholders in a dynamic and uncertain environment where new systems are added and current systems are removed continuously and on their own volition. is requires effective evolution management at the SoS architectural level with adequate support of process, methods, and tools. is paper follows the principle of Model-Based Systems Engineering (MBSE) and develops a holistic framework integrating MBSE conceptual representations and approximate dynamic programming (ADP) to support the SoS evolution. e conceptual models provide a common architectural representation to improve communication between various decision makers while the dynamic optimization method suggests evolution planning decisions from the analytical perspective. e Department of Defense Architecture Framework (DoDAF) models using Systems Modeling Language (SysML) are used as MBSE artifacts to connect with ADP modeling elements through DoDAF metamodels to increase information traceability and reduce unnecessary information loss. Using a surface warfare SoS as an example, this paper demonstrates and explains the procedures of developing DoDAF models, mapping DoDAF models to ADP elements, formulating ADP formulation, and generating evolutionary decisions. e effectiveness of using ADP in supporting evolution to achieve a near-optimal solution that can maximize the SoS capability over time is illustrated by comparing ADP solution to other alternative solutions. e entire framework also sheds light on bridging the DoDAF-based conceptual models and other mathematical optimization methods.

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Section: System-of-systems Evolutionmentioning

confidence: 99%

Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution

2020

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“…Before that, we first propose a new SoS model enabling to model more expressive problems than existing SoS models ((Acheson et al, 2012) and (Baldwin and Sauser, 2009)). Indeed, these models do not enable to take into account the concept of environment of a SoS.…”

Section: Saphesia Modelmentioning

confidence: 99%

“…This paper presents satisficing game that is the basis of the SoS collaboration formation heuristic presented in (Caffall and Michael, 2009). Finally, our model is more adequate than existing SoS models presented in (Acheson et al, 2012) and (Baldwin and Sauser, 2009) because we have added the concept of resource (section 3.1) which is essential to model UAV position. Furthermore, the concept of environment has been added to model more interesting models.…”

Section: Problem Descriptionmentioning

confidence: 99%

Cooperative Multi-agent Approach for Computational Systems of Systems Architecting

Bouziat

Combettes

Camps

et al. 2017

Proceedings of the 9th International Conference on Agents and Artificial Intelligence

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 18891The contribution was presented at ICAART 2017 : http://www.icaart.org/?y=2017 Abstract: This paper addresses the modeling and design of Systems of Systems (SoS). It presents and illustrates a new generic model to describe formally such systems. This model is used to propose a SoS architecting approach based on adaptive multi-agent systems. In this approach, each component system composing the SoS uses a local cooperative decision process in order to interact with other systems and to collectively give rise to a relevant overall function at the SoS level. The proposed model as well as the proposed approach are instantiated with a simulated unmanned aerial vehicle scenario and compared with another approach dealing with collaboration between systems in a SoS.

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“…Ricci et al discuss designing for evolvability of their SoS in a wave model and playing it out several cycles in the future, evaluating cost and performance. [34] Because SoS are complex, there are many ways to look at them, with no dominant theory yet; this is why we are pursuing this direction of research [35].…”

Section: Sos Acquisition Managermentioning

confidence: 99%

“…. Most recently, genetic algorithms (GA) was also used as a methodology within a tool suite of agent base modeling (ABM) for system of systems (SoS) evolution, where the impact of constituent systems are thought not to be well understood with respect to the overall system of systems capabilities [35].…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

An Advanced Computational Approach to System of Systems Analysis & Architecting Using Agent-Based Behavioral Model: Phase 2

Dağli¹

2013

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Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. REPORT DATE NOV 20132. REPORT TYPE SUPPLEMENTARY NOTES ABSTRACTThe goal of this research is to model the evolution of the architecture of an acknowledged Systems of Systems (SoS) that accounts for the ability and willingness of constituent systems to support the SoS capability development. Since DoD SoS development efforts do not typically follow the program of record acquisition process described in DoDI 5000.02, the Wave Model proposed by Dahmann and Rebovich is used as the basis for this research on SoS capability evolution. The Wave Process Model provides a framework for an agent-based modeling methodology, which is used to abstract the non-utopian behavioral aspects of the constituent systems and their interactions with the SoS. In particular, the research focuses on the impact of individual system behavior on the SoS capability and architecture evolution processes. This material has been approved for public release and unlimited distribution except as restricted below.Internal use:* Permission to reproduce this material and to prepare derivative works from this material for internal use is granted, provided the copyright and "No Warranty" statements are included with all reproductions and derivative works.External use:* This material may be reproduced in its entirety, without modification, and freely distributed in written or electronic form without requesting formal permission. Permission is required for any other external and/or commercial use. Requests for permission should be directed to the Systems Engineering Research Center at dschultz@stevens.edu * These restrictions do not apply to U.S. government entities. WHS TO 029, RT 044 UNCLASSIFIED Executive SummaryA major challenge to the successful planning and evolution of an Acknowledged System of Systems (SoS) is the current lack of understanding of the impact that the presence or absence of a set of constituent systems has on the overall SoS capability. Since the candidate elements of a SoS are fully functioning, stand-alone systems in their own right; they have goals and objectives of their own to satisfy, some of which may compete with those of the overarching SoS. These system-level concerns drive decisions to participate (or not) in the So...

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Understanding System of Systems Development Using an Agent- Based Wave Model

Cited by 26 publications

References 10 publications

Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution

Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution

Cooperative Multi-agent Approach for Computational Systems of Systems Architecting

An Advanced Computational Approach to System of Systems Analysis & Architecting Using Agent-Based Behavioral Model: Phase 2

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