Saurabh Mittal

MITRE

Complex systems have been studied by researchers from every discipline: biology, chemistry, physics, sociology, mathematics and economics and more. Depending upon the discipline, complex systems theory has accrued many flavors. We are after a formal representation, a model that can predict the outcome of a complex adaptive system (CAS). In this art...

According to Ashby, emergent behavior manifest itself due to a lack of understanding of the system. The problem while apparent in monolithic systems takes on center-stage in a system of system (SoS), components of which are geographically displaced and have independent managerial, evolutionary and operational controls. The emergent behavior in SoS...

Modeling and Simulation(M&S) has recently been applied to explore the nature of emergent behavior in complex systems engineering (CSE). M&S, along with Big Data technologies are at the forefront of such exploration and investigation. In the text: Emergent Behavior in Complex Systems Engineering: A Modeling and Simulation Approach, edited by Saurabh...

Autonomous and AI-enabled systems present a challenge for integration within the System of Sys-tems (SoS) paradigm. A full system of systems (SoS) testbed is necessary to verify the integrity of a given system and preserve the modularization and accountability of its constituent systems. This integrated system needs to support iterative, continuous...

The limitations of model-based support for engineering complex systems include limited capability to develop multifaceted models as well as their analysis with robust reliable simulation engines. Lack of such Modeling and Simulation (M&S) infrastructure leads to knowledge gaps in engineering such complex systems and these gaps appear as epistemolog...

Modeling and Simulation (M&S) is finding increasing application in development and testing of command and control systems comprised of information-intensive component systems. Achieving interoperability is one of the chief System of Systems (SoS) engineering objectives in the development of command and control (C2) capabilities for joint and coalit...

Modeling and Simulation (M&S) for system design and prototyping is practiced today both in the industry and academia. M&S are two different areas altogether and have specific objectives. However, most of the times these two separate areas are taken together. The developed code is tightly woven around both the model and the underlying simulator that...

Discrete EVent Specification (DEVS) environments are known to be implemented over middleware systems such as HLA, RMI, CORBA and others. DEVS exhibits concepts of systems theory and modeling and supports capturing the system behavior from the physical and behavioral perspectives. Further, they are implemented using Object-oriented languages like Ja...

Cloud simulation environments today are largely employed to model and simulate complex systems for remote accessibility and variable capacity requirements. In this regard, scalability issues in Modeling and Simulation (M\&S) computational requirements can be tackled through the elasticity of on-demand Cloud deployment. However, implementing a high...

The SCS M&S Body of Knowledge is a living concept, and core research areas are among those that will drive its progress. In this chapter, conceptual modeling constitutes the first topic, followed by the quest for model reuse. As stand-alone applications become increasingly rare, embedded simulation is of particular interest. In the era of big data,...

This chapter of the SCS M&S Body of Knowledge summarizes philosophical foundations that are only partially addressed in other chapters in a constrained manner. It starts with a philosophical discussion of simulation epistemology, including some idea about the role of ontologies as well. A timeline on scientific research and method development shows...

The increase in computational capabilities affects the simulation domain. This chapter of the SCS M&S Body of Knowledge looks in the state of the art of digital simulation, mobile simulation, and wearable simulation. It further describes cloud-based simulation and high-performance simulation, with additional sections on parallel evolutionary algori...

Employing Modeling and Simulation (M&S) extensively to analyze and develop complex systems is the norm today. The use of robust M&S formalisms and rigorous methodologies is essential to deal with complexity. Among them, the Discrete Event System Specification (DEVS) provides a solid framework for modeling structural, behavior and information aspect...

Cloud infrastructure provides rapid resource provision for on-demand computational requirements. Cloud simulation environments today are largely employed to model and simulate complex systems for remote accessibility and variable capacity requirements. In this regard, scalability issues in Modeling and Simulation (M&S) computational requirements ca...

This comprehensive book examines a range of examples, prepared by a diverse group of academic and industry practitioners, which demonstrate how cloud-based simulation is being extensively used across many disciplines, including cyber-physical systems engineering. This book is a compendium of the state of the art in cloud-based simulation that instr...

Cyber Physical Systems (CPS) are inherently distributed in nature; that is, the constituent systems are separated by geographical distances. This implies that there is always latency in communication exchanges between the system components. Various mechanisms such as frequency of updates, dead reckoning, and communication reliability are used to ad...

Cyber-Physical Systems (CPS) are complex systems that have two essential elements: the cyber element and the physical element. These are analogous to the early hardware/software (HW/SW) systems that predated the internet. CPS are fundamentally HW/SW systems with an additional capability of being remotely controlled, which introduces a significant a...

This book provides the state-of-the-art in methods and technologies that aim to elaborate on the modeling and simulation support to cyber physical systems (CPS) engineering across many sectors such as healthcare, smart grid, or smart home. It presents a compilation of simulation-based methods, technologies, and approaches that encourage the reader...

Cyber Physical Systems (CPS) are systems that bring together computational and physical worlds (through sensing and actuation). The emerging Internet of Things (IoT) ecosystem is a phenomenon already in the process of deployment. IoT has the same fundamental characteristics as CPS but at a larger scale of usage and deployment. The convergence of In...

This chapter is summarizing the research ideas explicitly and implicitly discussed in the expert contributions to this book. It is meant to provide a repository of research ideas for academia and industry to meet the current and future requirements. The chapter elaborates on seven themes: common formalism, complex environments, complexity toolbox,...

Cyber Physical Systems (CPS) are hybrid systems comprising multiple components and many other combinations of various integrated but heterogeneous computational and physical capabilities. Todays embedded system such as iPhones and smart watches have integrated hardware and software solutions. There are engineering methodologies available to develop...

This book provides the state-of-the-art in methods and technologies that aim to elaborate on the modeling and simulation support to cyber physical systems (CPS) engineering across many sectors such as healthcare, smart grid, or smart home. It presents a compilation of simulation-based methods, technologies, and approaches that encourage the reader...

Complex systems are everywhere, in both natural and artificial world. One of the characteristic properties of complex systems is the manifestation of emergent behavior that continuously keeps the system evolving. Many times, this emergent behavior is the very reason for the systems’ survival. To perform complex systems engineering for artificial sy...

Conference Proceedings

Summary of the book: Emergent Behavior in Complex Systems Engineering: A Modeling and Simulation Approach

The increasing popularity of the Internet of Things (IoT) emphasizes that heterogeneous systems are the norm today. A system deployed in a netcentric environment eventually becomes a part of a system of systems (SoS). This SoS may also incorporates adaptive and autonomous elements (such as systems that have different levels of autonomy and situated...

This chapter introduces simple, complicated, and complex system definitions and shows how these system classes are related to simple, weak, strong, and spooky emergence, and which systems engineering methods can be applied to support the detection, understanding, and management of such emergence. It considers the purpose of systems engineering, as...

This paper evaluates the state of the art of hybrid simulation support for cyber physical systems. The traditional definition for hybrid simulation is expanded to include recent research on multi-paradigm and other multi-faceted modeling approaches. Based on the review of current approaches, the focus of simulation support lies first in providing a...

Systems of Systems (SoS) that include intelligence and adaptability exhibit high complexity that cannot be easily tackled using classic system engineering techniques. Recent model-based system engineering has also proved inadequate due to lack of a full-strength modeling and simulation (M&S) computational substrate. Such full-strength M&S support c...

A recent paper laid a systems theoretic foundation for understanding how human language could have emerged from prelinguistic elements. The systems theoretic approach to incorporating emergence (as a construct) to understand a complex phe- nomenon first required the formulation of a system model of the phenomena. Having the correct formal system sp...

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Induced emergence is presented as a consequence of goal-directed steering of social systems. Multimodels offer a rich paradigm to model complex systems including complex social systems. Thirty types of multimodels are presented in an ontology-based dictionary where their definitions are given with their taxonomy. Formal modeling incorporating model...

In this chapter, we attempt to set the research agenda on emergence in the medium and long term. We first summarize the view of emergence from the authors in this book and conclude that almost all of them are focused on epistemological emergence, which results in better understand systems but fails in explaining the emergence of new categories as w...

The ‘Advances in the State of the Art of Modeling and Simulation’ special issue is in two parts. The first part covers the subject of hybrid systems modeling.1–3. It comprises five papers published in the preceding issue of the journal.4–8 This part includes two additional papers employing discrete event system specification (DEVS) formalism. An ov...

A comprehensive text that reviews the methods and technologies that explore emergent behavior in complex systems engineering in multidisciplinary fields In Emergent Behavior in Complex Systems Engineering, the authors present the theoretical considerations and the tools required to enable the study of emergent behaviors in manmade systems. Informat...

The technical aspects of the essence of simulation are elaborated based on the following definition: simulation is performing a goal-directed experimentation or gaining experience under controlled conditions by using dynamic models either to develop/enhance skills or for entertainment; where a dynamic model denotes a model for which behaviour and/o...

The ‘Advances in the State of the Art of Modeling and Simulation’ special issue is in two parts. The first part comprises five papers on hybrid systems modeling,1–3 which is the combined application of modeling and simulation with methods and techniques from disciplines such as computer science/applied computing, business analytics, data science, o...

Model-based paradigm has been adopted by a number of disciplines since its introduction in the late 70s. After a brief history on how model-based approach started in simulation, the merit and the spread of the model-based approach are described. The concept of model is subsumed in simulation, but many times employing just the model-based approach d...

Simulation is vital to many disciplines as has been shown throughout the book. Future specialists in every domain must include modeling and simulation (M&S) as integral part of their learning, education, and teaching the discipline itself. This fact has been accepted by various institutions, universities, and research centers as they incorporate M&...

Complex Adaptive Systems (CAS) are systems that display two primary characteristics: emergent behavior, and adaptive behavior. Emergent behavior manifests in a system comprising of large number of components, often considered as agents, engaged in multi-level interactions. Adaptive behavior manifests at the agent–environment boundary when the agent...

The aims of this chapter are: (1) To provide a comprehensive view of the stages of the evolution of simulation. (2) To emphasize the phenomenal developments in many aspects of simulation which made it an important and even a vital infrastructure for many disciplines. (3) To underline the fact that the transition from “model-based” paradigm to “simu...

This invaluable text/reference reviews the state of the art in simulation-based approaches across a wide range of different disciplines, and provides evidence of using simulation-based approaches to advance these disciplines. Highlighting the benefits that simulation can bring to any field, the volume presents case studies by the leading experts fr...

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This chapter recognizes that contemporary model-based system engineering must be robustly supported by modeling and simulation (M&S) professionals armed with theory, concepts, and tools up to the challenges of Cyber environments replete with multiple subject matter experts (SMEs) in any given scenario. It also aims to establish the need for formal...

In the Internet of Things (IoT) era, there is growing interest in wireless monitoring sensors for detection, classification and prediction of health symptoms. The prediction of symptoms in chronic diseases such as migraines brings new hope to improve patients' lives. The prediction of a migraine symptomatic event through monitoring hemodynamic vari...

Many have proposed that responsive load provided by distributed energy resources (DERs) and demand response (DR) are an option to provide flexibility to the grid and especially to distribution feeders. However, because responsive load involves a complex interplay between tariffs and DER and DR technologies, it is challenging to test and evaluate op...

The discrete event system specification formalism, which supports hierarchical and modular model composition, has been widely used to understand, analyze and develop a variety of systems. Discrete event system specification has been implemented in various languages and platforms over the years. The DEVStone benchmark was conceived to generate a set...

Design and development of hard Real-Time (RT) embedded systems present several crucial requirements regarding criticality and timeliness of these systems. Formal methods have been presented as a promising alternative to deal with the design issues of these applications. However, these formal method do not scale well in complex systems. Modeling and...

The Discrete EVent System (DEVS) specification has been implemented in various platforms and languages over the years. However, each implementation has been tightly coupled with the underlying syntactical language. The DEVS Modeling Language (DEVSML) is based on meta-modeling concepts that provide a Domain-Specific-Language (DSL) for DEVS model des...

System of Systems can be classified as virtual, collaborative, acknowledged and directed per the MITRE System Engineering Guide. Emergent behavior can be classified as simple, weak, strong and spooky. While simple and weak emergent behavior can be analyzed using modeling and simulation practices, strong emergent behavior cannot be modeled due to ex...

http://www.worldscientific.com/toc/ijmssc/07/01

Models have demonstrated proven benefits in specific aspects of the engineering process. Mechanical models, performance models, algorithmic models, systems engineering architecture models and others have proven useful and even perhaps indispensable. Models provide value at different points in the lifecycle with some supporting design and architectu...

Energy systems integration combines energy carriers, including electricity, with infrastructures, to maximize efficiency and minimize waste. In order to study systems at a variety of physical scales—from individual buildings to distribution systems—interconnected through these energy infrastructures, NREL is developing an Integrated Energy System M...

The combination of distributed energy resources (DER) and retail tariff structures to provide benefits to both utility consumers and the utilities is not well understood. To improve understanding, an Integrated Energy System Model (IESM) is being developed to simulate the physical and economic aspects of DER technologies, the buildings where they r...

This chapter provides background and an overview on systems theory, live, virtual, and constructive (LVC) distributed mission operations (DMO) environment, linguistic levels of interoperability, and how the theory of modeling and simulation (M&S) aids the development of interoperable systems. It describes the Model-Based Systems Engineering (MBSE)...

Cloud-based M&S can have many forms, from hardware as a service or cloud-based data for M&S applications to providing M&S as a service. In order to be able to compose such cloud-based M&S services, these services not only need to be able to exchange data and use such exchanged data, they also must represent truth consistently. Current paradigms are...

Sociotechnical systems pervade every facet of our life today. These IT systems interact with live users that result in emergent behaviors leading to their classification as complex adaptive systems (CAS). Cyber-CAS (CyCAS) exists in contemporary society when such systems have Internet as their platform. Modeling and Simulation (M&S) for CyCAS is ex...

Complex natural systems are natural systems that display strong emergent behavior. Adaptive agents in a resource limited environment optimize their behavior by processing only the most relevant information, i.e., activating the most germane components, learned or evolved from previous experience, thereby responding optimally with least expenditure...

Sustainable natural systems require energy. This requirement of energy is proportional to the activity they manifest. In a scalable self-similar artificial system, information gateways at every level must limit the information/activity to-from their subsystems based on computational algorithms. We discuss some of the implemented algorithms in these...

Model-Based Systems Engineering (MBSE) employs model-based technologies and established systems engineering practices. Model-Driven Engineering (MDE) provides various concepts to automate model based practices using metamodeling. We describe the DEVS Unified Process (DUNIP) that aims to bring together MBSE and MDE as Model-driven Systems Engineerin...

Intelligence can be defined as an emergent property in some types of complex systems and may arise as a result of an agent's interactions with the environment or with other agents either directly or indirectly through changes in the environment. Within this perspective, intelligence takes the form of an 'observer' phenomenon; externally observed at...

Artificial systems that generate contingency-based teleological behaviors in real-time, are difficult to model. This chapter describes a modeling and sim-ulation (M&S) framework designed specifically to reduce this difficulty. The de-scribed Knowledge-based Contingency-driven Generative Systems (KCGS) frame-work combines aspects of SES theory, DEVS...

This paper presents a revised version of DEVSML stack. The earlier version introduced the concept of transparent simulators in a netcentric domain. This version of DEVSML 2.0 stack introduces the transparent modeling concept and how a platform independent DEVS Modeling Language based on Finite Deterministic DEVS can help achieve model interoperabil...

New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated Data Types (DDTs) to store their data. The optimization of DDTs for each target embedded system is a time-consuming process due to the large searching space of possible DDTs implementations. This results in the minimization of embedded design variables...

Industry and government are spending extensively to transition their business processes and governance to Service Oriented Architecture (SOA) implementations for efficient information reuse, integration, collaboration and cost-sharing. SOA enables orchestrating web services to execute such processes using Business Process Execution Language (BPEL)....

Air Force Research Lab (AFRL) research efforts to transition cognitive modeling from the laboratory to operational environments are finding that available architectures and tools are difficult to extend, lack support for interoperability standards, and struggle to scale. This paper describes a component-based modeling and simulation framework that...

Air Force Research Lab (AFRL) research efforts employing cognitive and behavioral modeling are growing in scope and complexity as they work to integrate models into larger distributed systems as cognitive agents, synthetic teammates or human operator surrogates. Efforts to transition cognitive modeling from the laboratory to operational environment...

Air Force Research Lab (AFRL) research efforts to transition cognitive modeling from the laboratory to operational environments are finding that available architectures and tools are difficult to extend, lack support for interoperability standards, and struggle to scale. This paper describes a component-based cognitive modeling and simulation frame...

Artificial systems that generate contingency-based teleological behaviors in real-time, are difficult to model. This chapter describes a modeling and simulation (M&S) framework designed specifically to reduce this difficulty. The described Knowledge-based Contingency-driven Generative Systems (KCGS) framework combines aspects of SES theory, DEVS-ba...

Invited presentation to US Air Force Research Lab, 711th Human Performance Wing and European Office of Aerospace Research and Development,

With the modernization of Department of Defense (DoD) systems and the growing complexity of communication equipment, traditional test methods and processes have to evolve in order to maintain their effectiveness. DoD acquisition policy requires the use of modeling and simulation (M&S) in all phases of system development life-cycles in order to ensu...