A Cooperative SoS Architecting Approach Based On Adaptive Multi-Agent Systems.

This paper focuses on Systems of Systems (SoS) modeling and architecting. SoS architecting deals with the way that independent components of a SoS can be dynamically structured and can change autonomously their interactions in an efficient manner to fulfill the goal of the SoS and to cope with an evolving environment. In this context we defined a new model called SApHESIA (SoS Architecting HEuriStIc based on Agents) focusing on the environment and its dynamics. We also proposed a cooperative heuristic to control interactions exchanges between components. These contributions are then instantiated to a case study and evaluated through two scenarii. Obtained results are finally discussed and some perspectives are given

Flexible and Intelligent Learning Architectures for SOS (FILA-SoS)

Multi-faceted systems of the future will entail complex logic and reasoning with many levels of reasoning in intricate arrangement. The organization of these systems involves a web of connections and demonstrates self-driven adaptability. They are designed for autonomy and may exhibit emergent behavior that can be visualized. Our quest continues to handle complexities, design and operate these systems. The challenge in Complex Adaptive Systems design is to design an organized complexity that will allow a system to achieve its goals. This report attempts to push the boundaries of research in complexity, by identifying challenges and opportunities. Complex adaptive system-of-systems (CASoS) approach is developed to handle this huge uncertainty in socio-technical systems

Computational intelligence based complex adaptive system-of-systems architecture evolution strategy

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations 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 program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. --Abstract, page iii

Understanding Behavior of System of Systems Through Computational Intelligence Techniques

The world is facing an increasing level of systems integration leading towards systems of systems (SoS) that adapt to changing environmental conditions. The number of connections between components, the diversity of the components and the way the components are organized can lead to different emergent system behavior. Therefore, the need to focus on overall system behavior is becoming an unavoidable issue. The problem is to develop methodologies appropriate for better understanding behavior of system of systems before the design and implementation phase. This paper focuses on computational intelligence techniques used for analysis of complex adaptive systems with the aim of identifying areas that need methodology customization for SoS analysis

Architecting system of systems: artificial life analysis of financial market behavior

This research study focuses on developing a framework that can be utilized by system architects to understand the emergent behavior of system architectures. The objective is to design a framework that is modular and flexible in providing different ways of modeling sub-systems of System of Systems. At the same time, the framework should capture the adaptive behavior of the system since evolution is one of the key characteristics of System of Systems. Another objective is to design the framework so that humans can be incorporated into the analysis. The framework should help system architects understand the behavior as well as promoters or inhibitors of change in human systems. Computational intelligence tools have been successfully used in analysis of Complex Adaptive Systems. Since a System of Systems is a collection of Complex Adaptive Systems, a framework utilizing combination of these tools can be developed. Financial markets are selected to demonstrate the various architectures developed from the analysis framework --Introduction, page 3

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

A 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 SoS. Individual systems typically must be requested to join the SoS construct, and persuaded to interface and cooperate with other Systems to create the “new” capability of the proposed SoS. Current SoS evolution strategies lack a means for modeling the impact of decisions concerning participation or non-participation of any given set of systems on the overall capability of the SoS construct. Without this capability, it is difficult to optimize the SoS design. The goal of this research is to model the evolution of the architecture of an acknowledged SoS that accounts for the ability and willingness of constituent systems to support the SoS capability development. Since DoD Systems of Systems (SoS) development efforts do not typically follow the normal program 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 nonutopian 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. A generic agent-based model (ABM) skeleton structure is developed to provide an Acknowledged SoS manager a decision making tool in negotiating of SOS architectures during the wave model cycles. The model provides an environment to plug in multiple SoS meta-architecture generation multiple criteria optimization models based on both gradient and non-gradient descent optimization procedures. Three types of individual system optimization models represent different behaviors of systems agents, namely; selfish, opportunistic and cooperative, are developed as plug in models. ABM has a plug in capability to incorporate domain-specific negotiation modes and a fuzzy associative memory (FAM) to evaluate candidate architectures for simulating SoS creation and evolution. The model evaluates the capability of the evolving SoS architecture with respect to four attributes: performance, affordability, flexibility and robustness. In the second phase of the project, the team will continue with the development of an evolutionary strategies-based multi-objective mathematical model for creating an initial SoS meta architecture to start the negotiation at each wave. A basic generic structure will be defined for the fuzzy assessor math model that will be used to evaluate SoS meta architectures and domain dependent parameters pertaining to system of systems analysis and architecting through Agent Based Modeling. The work will be conducted in consideration of the national priorities, funding and threat assessment being provided by the environment developed for delivery at end of December 2013

A Cooperative Architecting Procedure for Systems of Systems Based on Self-Adaptive Multi-Agent Systems

Depuis la seconde guerre mondiale, l’ingénierie des systèmes a permis le développement de méthodologies pour contrôler le développement de systèmes et de projets de plus en plus complexes. En 1990, la chute de l’URSS a provoqué un changement de doctrine militaire aux Etats-Unis en passant d’une confrontation bipolaire à une mondialisation des conflits comportant une grande variété de menaces. Sa nouvelle doctrine était de faire collaborer ses systèmes de défense existants pour produire un système de défense de haut niveau, décentralisé, adaptable et composé de systèmes indépendants. C’est l’apparition du concept de Système de Systèmes (SdS).Cette thèse de doctorat propose un nouveau modèle de SdS appelé SApHESIA (SoS ArchitectingHEuriStIc based on Agent), ainsi qu’une nouvelle méthodologie d’architecture. Cette nouvelle méthodologie est basée sur une coopération complète entre tous les composants du SdS, lui permettant d’évoluer de lui-même afin de faire face à des événements inattendus de son environnement tels que des menaces. Enfin, ce travail est testé à travers 4exemples issus de différents domaines (militaire, logistique et exploratoire).Since the World War II, researchers have tended to develop methodologies and tools tobuild and control the development of more and more complex systems and projects. Thisinter-disciplinary research area has been called Systems Engineering (SE) and continues tobe developed nowadays. In 1990, the fall of USSR led the US Department of Defense (DoD)to re-think its defense doctrine and to switch from a one opponent confrontation to a globalizationof conflicts with a huge variety of scenarios. Its idea was to re-use and join itsdefense systems by producing a huge, decentralized and adaptive defense system that iscomposed of existing and independents (complex) systems. This is the apparition of theSystem of Systems (SoS) concept. After 2000’s, this concept spreads in civil domains suchas crisis management or logistic systems. More precisely, a SoS is a complex system characterizedby the particular nature of its components: these latter, which are systems, tend tobe managerially and operationally independent as well as geographically distributed. Thisspecific characterization led to re-think research areas of classic SE such as definition, taxonomy,modeling, architecting and so on. SoS architecting focuses on the way independentcomponents of a SoS can be dynamically structured and can change autonomously theirinteractions in an efficient manner to fulfill the goal of the SoS and to cope with the highdynamics of the environment. This PhD thesis mainly focuses on two SoS research areas: 1)SoS modeling and 2) SoS architecting. To achieve the first point, we propose a new modelcalled SApHESIA (SoS Architecting HEuriStIc based on Agent). We have used set theoryand ABM (Agent-Based Model) paradigm to define this model that takes into account thecharacteristics of SoS. Secondly, we propose a new SoS architecting procedure based on theAdaptive Multi-Agent System (AMAS) approach that advocates full cooperation betweenall the components of the SoS through the concept of criticality. This criticality is a metricthat represents the distance between the current state of a component and its goals. In thisprocedure, the SoS architecture evolves over time to self-adapt to the dynamics of the environmentin which it is plunged, while taking into account the respective local goals of itscomponents. Finally we instantiate this model and this procedure through 4 examples fromdifferent domains (military, logistics and exploratory missions) and validate the feasibility,the efficiency, the effectiveness and the robustness of the SoS architecting procedure we havedeveloped and proposed

A Cooperative Architecting Procedure for Systems of Systems Based on Self-Adaptive Multi-Agent Systems

Depuis la seconde guerre mondiale, l’ingénierie des systèmes a permis le développement de méthodologies pour contrôler le développement de systèmes et de projets de plus en plus complexes. En 1990, la chute de l’URSS a provoqué un changement de doctrine militaire aux Etats-Unis en passant d’une confrontation bipolaire à une mondialisation des conflits comportant une grande variété de menaces. Sa nouvelle doctrine était de faire collaborer ses systèmes de défense existants pour produire un système de défense de haut niveau, décentralisé, adaptable et composé de systèmes indépendants. C’est l’apparition du concept de Système de Systèmes (SdS).Cette thèse de doctorat propose un nouveau modèle de SdS appelé SApHESIA (SoS ArchitectingHEuriStIc based on Agent), ainsi qu’une nouvelle méthodologie d’architecture. Cette nouvelle méthodologie est basée sur une coopération complète entre tous les composants du SdS, lui permettant d’évoluer de lui-même afin de faire face à des événements inattendus de son environnement tels que des menaces. Enfin, ce travail est testé à travers 4exemples issus de différents domaines (militaire, logistique et exploratoire).Since the World War II, researchers have tended to develop methodologies and tools tobuild and control the development of more and more complex systems and projects. Thisinter-disciplinary research area has been called Systems Engineering (SE) and continues tobe developed nowadays. In 1990, the fall of USSR led the US Department of Defense (DoD)to re-think its defense doctrine and to switch from a one opponent confrontation to a globalizationof conflicts with a huge variety of scenarios. Its idea was to re-use and join itsdefense systems by producing a huge, decentralized and adaptive defense system that iscomposed of existing and independents (complex) systems. This is the apparition of theSystem of Systems (SoS) concept. After 2000’s, this concept spreads in civil domains suchas crisis management or logistic systems. More precisely, a SoS is a complex system characterizedby the particular nature of its components: these latter, which are systems, tend tobe managerially and operationally independent as well as geographically distributed. Thisspecific characterization led to re-think research areas of classic SE such as definition, taxonomy,modeling, architecting and so on. SoS architecting focuses on the way independentcomponents of a SoS can be dynamically structured and can change autonomously theirinteractions in an efficient manner to fulfill the goal of the SoS and to cope with the highdynamics of the environment. This PhD thesis mainly focuses on two SoS research areas: 1)SoS modeling and 2) SoS architecting. To achieve the first point, we propose a new modelcalled SApHESIA (SoS Architecting HEuriStIc based on Agent). We have used set theoryand ABM (Agent-Based Model) paradigm to define this model that takes into account thecharacteristics of SoS. Secondly, we propose a new SoS architecting procedure based on theAdaptive Multi-Agent System (AMAS) approach that advocates full cooperation betweenall the components of the SoS through the concept of criticality. This criticality is a metricthat represents the distance between the current state of a component and its goals. In thisprocedure, the SoS architecture evolves over time to self-adapt to the dynamics of the environmentin which it is plunged, while taking into account the respective local goals of itscomponents. Finally we instantiate this model and this procedure through 4 examples fromdifferent domains (military, logistics and exploratory missions) and validate the feasibility,the efficiency, the effectiveness and the robustness of the SoS architecting procedure we havedeveloped and proposed

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

System of Systems (SoS) development is a complex process that depends on the cooperation of various independent Systems[1]. SoS acquisition and development differs from that typical for a single System; it has been shown to follow a wave paradigm known as the Wave Model[2]. Agent based models (ABMs) consist of a set of abstracted entities referred to as agents, and a framework using simplified rules for simulating agent decisions and interactions. Agents have their own goals and are capable of perceiving changes in the environment. Systemic (global) behavior emerges from the decisions and interactions of the agents. This research provides a generic model of SoS development with a genetic algorithm and fuzzy assessor implemented in an agent based model. The generic SoS development follows the Wave Model. The genetic algorithm provides an initial SoS meta- architecture. The fuzzy assessor qualitatively evaluates SoS meta-architectures. The agent-based model implements the generic SoS development, the genetic algorithm, the fuzzy assessor, and independent SoS and system agents and shows the SoS development based on an initial set of conditions. A prototype model is developed to test the concept on a sample from the DoD Intelligence, Surveillance, and Reconnaissance (ISR) domain