Bernard Phillip ZeiglerThe University of Arizona | UA · Department of Electrical and Computer Engineering
Bernard Phillip Zeigler
Doctor of Philosophy
Chief Scientist, RTSync Corp.rtsync.com
About
715
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Introduction
1. Wikipedia article: http://en.wikipedia.org/wiki/Bernard_P._Zeigler
2. RTSync Chief Scientist: http://rtsync.com/
3. Computer Simulation Pioneer: http://d.lib.ncsu.edu/computer-simulation/videos/bernard-p-zeigler-interviewed-by-richard-e-nance-zeigler
4. ACIMS: https://acims.asu.edu/
Publications
Publications (715)
Download from: https://www.mdpi.com/2078-2489/12/12/531
The DEVS formalism has been recognized to support generic open architectures that allow incorporating multiple engineering domains within integrated simulation models. What is missing for accelerated adoption of DEVS-based methodology for intelligent cyberphysical system design is a set of bu...
Discrete Event System Specification (DEVS) Natural Language (DNL) implements the DEVS simulation formalism using a natural languagelike notation. However, DNL models can still be complex, involving multiple inputs/outputs, internal/external state transitions, and arbitrary Java code blocks, which steepens the learning curve and reduces the efficien...
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...
In the discipline and practice of Systems Engineering, we typically derive verification models based on implicit, heuristic assumptions rather than science-based approach. For example, when we define verification requirements, we may optionally define a desired fidelity of a verification model as to its representativeness to a final product in the...
Paratemporal methods based on tree expansion have proven to be effective in efficiently generating the trajectories of stochastic systems. However, combinatorial explosion of branching arising from multiple choice points presents a major hurdle that must be overcome to implement such techniques. In this paper, we tackle this scalability problem by...
Paratemporal methods based on tree expansion have proven to be effective in efficiently generating trajectories of stochastic systems. However, combinatorial explosion of branching arising from multiple choice points presents a major hurdle that must be overcome to implement such techniques. In this paper we tackle this scalability problem by devel...
Talk given to IEEE Southeastern Michigan Section Sept 19 2023
Model Based System Engineering (MBSE) emphasizes systematically using models throughout the design process
Modeling and simulation (M&S) helps MBSE to connect the stages of MBSE
Discrete Event Systems Specification (DEVS) models real systems for digital representation and simulation
Ob...
Commissioned by the Society for Modeling and Simulation International (SCS), this needed, useful new ‘Body of Knowledge’ (BoK) collects and organizes the common understanding of a wide collection of professionals and professional associations.
Modeling and simulation (M&S) is a ubiquitous discipline that lays the computational foundation for real...
Downloadable folder of hyperlinked explanations relating to DEVS and its basis in System Theory
Science areas supporting modeling and simulation are overviewed in this chapter of the SCS M&S Body of Knowledge. The areas are systems science and engineering, simulation programs for differential equation solution, key features of frequently used distributions in modeling and simulation, queueing theory, characteristics of queuing systems, and st...
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,...
The chapter on history of simulation is foundational contribution to the SCS M&S Body of Knowledge that reviews the development of the discipline. The development of continuous and event-oriented simulation with the support of accompanying languages is the topic of one section. How simulation evolved to support experiments and experimentation is an...
This chapter deals with models, data, and their relations and use. It introduces the big picture of the SCS M&S Body of Knowledge, providing taxonomies for models and their uses and resulting perceptions as well as an extensive section on data. It addresses the questions of modeling and various modeling formalisms, model engineering, and model cura...
This chapter of the SCS M&S Body of Knowledge begins with a section on the types and sources of various errors, including an extensive list of relevant terms. The need for reliability leads to a section on validation as well as a section on verification. It is closed by a section on failure avoidance.KeywordsModeling and simulationsources of errors...
In this chapter, we provide an introductory view for the scope of the SCS M&S Body of Knowledge, including the terminology. We provide a rationale for the theoretical basis of M&S and give an overview of the modeling and simulation framework (MSF) applied in many contributions, followed by the basic system entity structure (SES) concepts.KeywordsMo...
Fall detection (FD) systems enable rapid detection and intervention for people who experience falls, a leading threat to the elderlys health and autonomy. Most of these systems conform to an IoT reference architecture which may include multiple sensing mechanisms to balance the advantages and drawbacks of each alternative. However, developing such...
This article works toward a unification of two related concepts that underpin system-theory-based modeling and simulation–the hierarchy of system specifications and morphisms and the System Entity Structure (SES). The hierarchy organizes system specification along levels ranging from behavior to structure capturing increasing knowledge of the syste...
Systems thinking in a VUCA (Volatility, uncertainty, complexity and ambiguity) World requires representation of complexity
Modeling and Simulation (M&S) are widely used for computational experimentation with a view to understanding and dealing with complex systems
The Discrete Event System Specification (DEVS) formalism provides a computational ba...
This is the presentation of the paper with the same name.
Our objective is to show how the hierarchy of system specifications and morphisms affords a framework that supports modeling and simulation of mind/brain in a coherent manner. Such a framework provides a credible path for simulation/implementation of cognitive behavior at the level of neuron...
Simulation has proven to be a widely used tool for computational experimentation with a view to developing and implementing intelligent system designs.
The Discrete Event System Specification (DEVS) formalism supports generic open architectures that incorporate multiple engineering domains within integrated cyberphysical system designs.
Discrete...
Simulation has proven to be a widely used tool for computational experimentation with a view to developing and implementing intelligent system designs. The Discrete Event System Specification (DEVS) formalism supports generic open architectures that incorporate multiple engineering domains within integrated cyberphysical system designs. Here we dis...
We review Discrete-Event system Specification (DEVS) in the context of Model-based Systems Engineering (MBSE) and discuss an application of DEVS methodology to MBSE. We outline support for an envisioned MBSE development cycle of DEVS top-to-bottom MBSE capability and offer an example of mapping UML activity diagrams into executable activity-based D...
Update:
The first article at the bottom of the page:
https://www.mdpi.com/journal/information/special_issues/Simulation_Modelling
has been published. The first cfp was sent via:
https://www.researchgate.net/publication/360161125_Open_Special_Issue_Simulation_Modeling_Theory_and_Practice_Pushing_the_Boundaries_Message_from_the_Guest_Editors
There i...
The Discrete Event System Specification (DEVS) is a modeling formalism that supports a general methodology for describing discrete event systems with the capability to represent continuous, discrete, and hybrid systems due to its system theoretic basis. In this chapter, we discuss the use of DEVS as the basic modeling and simulation framework for M...
Achieving value-based healthcare – increasing quality, reducing cost, and spreading access – has proven to be extremely challenging. In recent years, a large variety of care coordination organizations have emerged at regional and national scales. Unfortunately, each such health entity lives in its own definition (silo) of care coordination leaving...
In this talk, we show how the two main and orthogonal, pillars of M&S theory – levels of system specification with associated morphisms, and systems specification formalisms – help develop models of complex intelligent systems. We discuss Discrete Event System Specification (DEVS) models that exhibit intelligent behaviors and can be developed, obse...
Model Based System Engineering (MBSE) refers to the trend to use models systematically throughout the design process. MBSE has been struggling to find a way to connect the blueprint models that describe the initial architecture with ways to check and evaluate these plans. Simulation has become the preferred means to support this goal. Discrete Even...
Featured Application: This research contributes toward the theoretical foundations of model-based systems engineering (MBSE) through combining the mathematical, system theoretic framework for MBSE developed by A. Wayne Wymore with the computational systems theory of Discrete Event System Specification (DEVS). This research leads to internally consi...
Abstraction and its concrete realization are essential for progress
Abstractions enable uncluttered thought while
concrete realizations are closer to reality but necessarily messy.
In computer science: Progression: abstraction => formalization => implementation is exemplified by Boole and Turing.
In Modeling and Simulation (M&S), abstractions sepa...
We propose an integrative environment for the modeling and simulation of activity specification. The devised approach relies on the DEVS (Discrete Event System Specification) formalism for the foundational semantics of the essential activity elements. The code generation takes place afterward, targeting specific DEVS-compliant modeling and simulati...
Despite significant advances in fields from neurophysiology to cognitive science, a wide gap remains between cognition and neural substrate.
The Discrete Event Systems Specification (DEVS) modeling abstraction characterizes neuronal elements as having discrete states, processing messages, and employing own memory while coordinating themselves in...
We formulate burst detection as perception of event sequences where a burst is characterized as a sub-sequence of events that are closely spaced in time (i.e., Inter-event separation is within a given duration). We define an I/O behavior function to represent the perception as a computation, provide DEVS models that generate these behaviors, and si...
Computations have been advocated as abstractions that can bridge the neural circuit to cognition gap, Here we demonstrate simple computation-like behaviors that are necessary to fully characterize order of arrival perceptions. We also provide system state-level models that produce these behaviors and prove their canonical minimal nature. Simple sim...
We present here a system morphism methodology to give insight into the lumping process of networks of linear systems. Mean field assumptions are summarized as an example of two particular/significant assumptions for lumping: Homogeneity and fixed-point preservation in the lumped network model. Behavioral homogeneity (all linear systems having the s...
Related Work on Regular Expressions, Automata, Neurons
Types of Iterative System Specification (ISS)
DEVS simulation of Hybrid ISS: Implementation in MS4 Me
Regular Language Realization at the DEVS Atomic and Network Level
Regular Language Realization in I/O Systems
Hybrid ISS framework for Realizing Neurocognitive Behavior
Conclusions and Further...
System Entity Structures (SES) are used to define families of systems. In this context they are employed in combination with a model base (MB) to describe a set of simulation models. Using a framework, simulation models are generated from the SES/MB in a goal-oriented manner, executed and their results analyzed. The entire process is automated, ite...
Outline:
Recommend new class of disease management models.
How to proceed? - New abstractions needed.
Continuity of Care abstraction formalized as Staged Pipeline model.
Taiwan COVID-19 response as case in point.
Crossproduct Interaction with disease propagation.
Simulation model-based Tracking/Intervention Decision Support.
Development status.
Mu...
System entity structure has been used since the 1970s as a formal ontology framework, axiomatically defined, to represent the elements of a system of systems and their hierarchical relationships resulting in a family of hierarchical models. One challenge with this approach is the process of exploring a family of hierarchical models, and selecting a...
Modeling and Simulation (M&S) represents a core capability needed to address today’s complex, adaptive, systems of systems (SoS) engineering challenges.
The limitations of Model-Based Systems Engineering (MBSE) include limited capability to develop multifaceted models, as well as their analysis with computationally powerful and correct simulation...
We discuss two scenarios involving simultaneous events modeled in Parallel Discrete Event System Specification (PDEVS).
They demonstrate PDEVS features of zero time advance, causation, confluent internal/external transitions, and multiple input handling.
Parallel and Distributed simulation methods are typically based on a one-dimensional time sta...
Theory of Modeling and Simulation (Third Edition) follows its predecessors in providing an authoritative and complete theoretical solution for researchers, graduate students and working engineers interested in posing and solving problems using the tools of computational modeling and simulation.
We discuss its main unifying concept, the iterative sy...
IEEE Distinguished Speaker: Prof Bernard Zeigler
Venue: MITA St Venera
Lecture: Digital Health: Systems-of Systems Modeling and Simulation for Coordinating the Coordinators
The Workshop on Modeling and Simulation of Software-Intensive Systems (MSSiS) is a forum for researchers and practitioners from both communities modeling and simulation. The goal of the workshop is to provide an environment for discussions on how to propose and/or adapt notations, techniques, and methods to foster the adoption of dynamic models in...
Outline: A short history of neuron element modeling; Computational Iterative System Paradigm; Previous presentations on ResearchGate; Artificial neural nets (ANN); Spiking Leaky Integrate and Fire (LIF) neurons; Behaviors that LIF neurons can’t display: Self organizing NN; Languages: Generators and Recognizers, System formulation; Revitalizing Klee...
Experimental finding point suggest that memory trace and timing mechanisms can be localized to individual cells.
In previous work, Part I, we modeled and simulated cell feedback protocols directly as DEVS Markov models.
Here we embed this model within a case study of an actual temporal choice experiment in which time intervals between events are us...
Neurons (in the cerebellum parietal cortex and hippocampus) have been observed to encode elapsed time.
Neurons ( e.g., cerebellar Purkinje cells) can learn to respond at a particular time that reflects the time between stimuli.
This implies that memory trace and timing mechanisms can be localized to individual cells.
Here we develop, and simulati...
Self-organizing neural nets (SONN) implement certain operations at a macro level that require complex protocols at the individual cell (micro) level.
Roughly a critical operation assumes that given an input (e.g. facial image), the first and second neurons closest to the input (in recognition space) can identify themselves.
This operation is easy t...
The progression of abstraction, formalization, and implementation have played a critical role in advancing the theory and practice of modeling and simulation. In this chapter, we first review the historical record to illustrate how this progression characterizes the pattern of development of both the precursors, and the essence, of discrete event s...
With the advent of Unmanned Autonomous Vehicles (UAV), new kinds of systems of systems (SoS) that provide specific services may be on the horizon. We recognize that beyond basic technology requirements, such UAV-based service systems may be subject to a multiplicity of system engineering objectives. An all-inclusive model would be able to provide t...
Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations, Third Edition, continues the legacy of this authoritative and complete theoretical work. It is ideal for graduate and PhD students and working engineers interested in posing and solving problems using the tools of logico-mathematical modeling and compute...
The development of care pathways is increasingly becoming an instrumental artefact towards improving the quality of care and cutting costs. This paper presents a framework that incorporates Simulation Modeling along with Machine Learning (ML) for the purpose of designing pathways and evaluating the return on investment of implementation. The study...
Achieving value-based healthcare, increasing quality, reducing cost, and spreading access has proven to be extremely challenging. Today's research is largely focused on singular risk factors addressed by specific medical interventions and clinical programs within siloed operational structures. As a result of such service fragmentation, effective ca...
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...