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Simulation Modeling Theory and Practice: Pushing the Boundaries
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Simulation Modeling Theory and Practice: Pushing the Boundaries

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Theory and Methodology".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 17939

Special Issue Editors

Prof. Dr. Bernard P. Zeigler

E-Mail Website1 Website2
Guest Editor
1. Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721, USA
2. RTSync Corp., Chandler, AZ 85226, USA
Interests: general/mathematical systems theory; theory of systems modeling and simulation; model-based system engineering; modeling and simulation software environments; DEVS and DEVS-based computational modeling; linking cognitive behavior to neural and other implementations
Prof. Dr. Tuncer Ören

E-Mail Website
Guest Editor
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada
Interests: agent-directed simulation; cognitive simulation; emotive simulation; ethics in simulation; failure avoidance and simulation; M&S Body of Knowledge; M&S terminology; ontology-based dictionaries; simulation-based disciplines; synergies of simulation; awareness, machine understanding, general/mathematical systems theories, and systems engineering
Prof. Dr. Andreas Tolk

E-Mail Website1 Website2
Guest Editor
The MITRE Corporation, 1001 Research Park Blvd #220, Charlottesville, VA 22911, USA
Interests: complex adaptive systems; simulation for policy decision making; artificial societies; human simulation; epistemology of simulation; simulation formalisms

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to collect outstanding articles that push the boundaries of modeling and simulation (M&S). In recent decades, modeling and simulation has evolved to the point where it is now a recognized discipline and provides infrastructure for disciplines spanning the whole spectrum of human knowledge, intellectual and practical effects. The term “modeling and simulation” grants equal stress on both modeling and simulation aspects of this discipline. The Modeling and Simulation Body of Knowledge (M&S BoK) is a living work in process with the goal of establishing a kernel of topics that categorically characterize the discipline of modeling and simulation as it drives the progress of multifold disciplines in science, engineering, and the arts. The M&S BoK is sponsored by the Society for Modeling and Simulation International (SCS), the premier technical society dedicated to advancing the use of M&S to solve real-world problems. The essence of M&S is the creation of conceptual representations of entities, relations, and processes describing a problem domain with the goal of making them computationally executable artifacts. Such simulation models can be used to perform experiments or to gain experience; both dimensions provide a multitude of possibilities. This Special Issue recognizes recent progress of M&S with a call to build on past advancements and further advance the boundaries of theory and practice in this field. In the same way that advancements in telescope technology open up new domains of astronomical investigation, authors should address how modeling and simulation can push the boundary from what is today only theoretically possible towards what can become practically possible in the future. Potential authors are urged to contact one of the SI editors indicating the general theme to be addressed and to request related material from the prepublication of the M&S BoK. Information on how to cite this material will be provided after publication arrangements for the M&S BoK are finalized with a major publisher.

Topics of interest are drawn from the M&S BoK. Suggested areas for the Special Issue include (but are not limited to) the following:

  • Theoretical, mathematical, and system foundations;
  • Model engineering and construction technologies;
  • Methodologies, methods, and algorithms for M&S applications;
  • Simulation experience and experimentation;
  • Unified conceptual representations for hybrid M&S;
  • Reliability and quality assurance, validation, and verification;
  • Philosophical questions in relation to M&S: the importannce of simulations to progress in science;
  • M&S in relation to artificial intelligence and data science;
  • Ethics in conduct of M&S;
  • Technical challenges in the simulation of autonomous, autonomic, and apoptotic systems;
  • M&S for civilian and military concerns in the cyber–physical era.

Prof. Dr. Bernard P. Zeigler
Prof. Dr. Tuncer Ören
Prof. Dr. Andreas Tolk
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • transdisciplinary modeling and simulation
  • modeling and simulation foundations
  • model engineering
  • modeling formalisms
  • modeling and simulation methodologies
  • simulation engineering
  • hybrid modeling and simulation
  • model validation
  • simulation verification
  • simulations in science
  • artificial intelligence in modeling and simulation
  • modeling and simulation ethics
  • cyber–physical systems simulation

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

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Research

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26 pages, 6031 KiB  
Article
Providing a User Extensible Service-Enabled Multi-Fidelity Hybrid Cloud-Deployable SoS Test and Evaluation (T&E) Infrastructure: Application of Modeling and Simulation (M&S) as a Service (MSaaS)
by Saurabh Mittal, Robert L. Wittman, John Gibson, Josh Huffman and Hans Miller
Information 2023, 14(10), 528; https://doi.org/10.3390/info14100528 - 28 Sep 2023
Cited by 2 | Viewed by 1744
Abstract
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. [...] Read more.
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 testing and development. This need war-rants the development of a virtual environment that provides the ground truth in a simulated sce-nario, interfaces with real-world data, and uses various domain-specific and domain-agnostic simulation systems for development, testing, and evaluation. These required features present a non-trivial challenge wherein constructive models and systems at different levels of fidelity need to interoperate to advance the testing, evaluation, and integration of complex systems. Such a virtual and constructive SoS architecture should be independent of the underlying computational infra-structure but must be cloud-enabled for wider integration of AI-enabled software components. This paper will present a modular Simulation, Experimentation, Analytics, and Test (SEAT) Lay-ered Architecture Framework, a 10-step methodology. This paper will also demonstrate a case study of a hybrid cloud-enabled simulation SoS that allows extensibility, composability, and de-ployability in different target environments. Full article
(This article belongs to the Special Issue Simulation Modeling Theory and Practice: Pushing the Boundaries)
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15 pages, 358 KiB  
Article
Toward a Simulation Model Complexity Measure
by J. Scott Thompson, Douglas D. Hodson, Michael R. Grimaila, Nicholas Hanlon and Richard Dill
Information 2023, 14(4), 202; https://doi.org/10.3390/info14040202 - 24 Mar 2023
Cited by 4 | Viewed by 2566
Abstract
Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity. This article offers an overview of the [...] Read more.
Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity. This article offers an overview of the complexity from a variety of perspectives and provides a body of knowledge with respect to the complexity of simulation models. The key terms model detail, resolution, and scope are defined. An important concept from algorithmic information theory, Kolmogorov complexity, and an application of this concept, normalized compression distance, are used to indicate the possibility of measuring changes in model detail. Additional research in this area can advance the modeling and simulation body of knowledge toward the practical application of measuring simulation model complexity. Examples show that KC and NCD measurements of simulation models can detect changes in scope and detail. Full article
(This article belongs to the Special Issue Simulation Modeling Theory and Practice: Pushing the Boundaries)
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16 pages, 3941 KiB  
Article
Towards a DEVS Model Management System for Decision-Making Web Applications
by Laurent Capocchi and Jean François Santucci
Information 2023, 14(2), 69; https://doi.org/10.3390/info14020069 - 26 Jan 2023
Viewed by 2342
Abstract
The discrete event system specification formalism introduced by Zeigler in the 1970s is ideally associated with new technological advances in the web to offer an almost quasi-automatic mechanism for exporting its simulation models associated with experimental frames into web apps. In this paper, [...] Read more.
The discrete event system specification formalism introduced by Zeigler in the 1970s is ideally associated with new technological advances in the web to offer an almost quasi-automatic mechanism for exporting its simulation models associated with experimental frames into web apps. In this paper, we show how, thanks to the association of certain current web concepts (cloud computing, application virtualization, etc.), discrete event system specification formalism makes it easier to develop web apps that use simulation models to assist decision-making. We propose a simulation model management system used by teams of data scientists, modelers, and developers (engineers) capable of building and deploying web applications from simulation models with minimal web development knowledge. Full article
(This article belongs to the Special Issue Simulation Modeling Theory and Practice: Pushing the Boundaries)
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15 pages, 4459 KiB  
Article
SES-X: A MBSE Methodology Based on SES/MB and X Language
by Kunyu Xie, Lin Zhang, Xin Li, Pengfei Gu and Zhen Chen
Information 2023, 14(1), 23; https://doi.org/10.3390/info14010023 - 29 Dec 2022
Cited by 5 | Viewed by 1934
Abstract
Model-based systems engineering (MBSE) is a leading paradigm for the analyses and development of complex systems. However, the development of modeling and simulation infrastructure supporting MBSE is lacking, which limits the application of MBSE. To address this problem, this paper proposes an SES-X [...] Read more.
Model-based systems engineering (MBSE) is a leading paradigm for the analyses and development of complex systems. However, the development of modeling and simulation infrastructure supporting MBSE is lacking, which limits the application of MBSE. To address this problem, this paper proposes an SES-X methodology that integrates system modeling (following SES philosophy) with system simulation (supported by X language) to support the full lifecycle of MBSE modeling, including system analysis, architecture decomposition, physical modeling, and simulation. In the process, SES-X performs two levels of model pruning for model verification and simulation efficiency. This paper also conducts a case study on a car model to illustrate the effectiveness of the SES-X methodology. Full article
(This article belongs to the Special Issue Simulation Modeling Theory and Practice: Pushing the Boundaries)
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20 pages, 3256 KiB  
Article
Extending the Hierarchy of System Specifications and Morphisms with SES Abstraction
by Bernard P. Zeigler
Information 2023, 14(1), 22; https://doi.org/10.3390/info14010022 - 29 Dec 2022
Cited by 1 | Viewed by 2090
Abstract
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 [...] Read more.
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 system input/output processing and state dynamics. The SES is a constructive ontology describing compositions of modular components via coupling of input/output ports. Toward unification of these concepts, we propose an abstraction of the SES called the MetaSES that supports the construction of complex systems of systems with multiple components belonging to specified classes. Moreover, we place the MetaSES within a computational framework with the goal of making it easier to design and build complex hierarchical DEVS models and to communicate their structures and intended behaviors to foster continued reuse and development. We discuss several examples of applications to illustrate how the MetaSES-based enhancement of the hierarchy of system specifications and morphisms helps to push the boundaries of complexity management in the theory and practice of modeling and simulation. Research directions stemming from the proposed concepts are suggested. Full article
(This article belongs to the Special Issue Simulation Modeling Theory and Practice: Pushing the Boundaries)
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15 pages, 1768 KiB  
Article
Simulation-Based Optimization: Implications of Complex Adaptive Systems and Deep Uncertainty
by Andreas Tolk
Information 2022, 13(10), 469; https://doi.org/10.3390/info13100469 - 30 Sep 2022
Cited by 6 | Viewed by 3370
Abstract
Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as [...] Read more.
Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about the system and the outcomes of interest. Complex adaptive systems under deep uncertainty must integrate the search for robust solutions by conducting exploratory modeling and analysis. This article visits both domains, shows what the new challenges are, and provides a framework to apply methods from operational research and complexity science to address them. With such extensions, simulation-based approaches will be able to support these new areas as well, although optimal solutions may no longer be obtainable. Instead, robust and sufficient solutions will become the objective of optimization processes. Full article
(This article belongs to the Special Issue Simulation Modeling Theory and Practice: Pushing the Boundaries)
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17 pages, 3716 KiB  
Concept Paper
Broad and Selectively Deep: An MRMPM Paradigm for Supporting Analysis
by Paul K. Davis
Information 2023, 14(2), 134; https://doi.org/10.3390/info14020134 - 18 Feb 2023
Cited by 1 | Viewed by 1619
Abstract
This paper discusses challenges for M&S if it is to be increasingly important to decision aiding and policy analysis. It suggests an approach that—from the outset of a policy analysis project—incorporates M&S of a varied resolution with the intent that (1) the results [...] Read more.
This paper discusses challenges for M&S if it is to be increasingly important to decision aiding and policy analysis. It suggests an approach that—from the outset of a policy analysis project—incorporates M&S of a varied resolution with the intent that (1) the results of analysis will be communicated with a relatively simple model and corresponding narrative that scans the system problem in breadth, having been informed by richer modeling, and (2) the broad view is supplemented by the selective detail (zooms) and selected change of the perspective as needed. This is not just a matter of “dumbing down” communication, but a matter of thinking about both forests and trees from the outset and about designing analytic tools accordingly. It will also enable exploratory analysis amidst uncertainty and disagreement, which is central to modern policy analysis and decision-aiding. All of this poses significant challenges for those who design and build M&S. Full article
(This article belongs to the Special Issue Simulation Modeling Theory and Practice: Pushing the Boundaries)
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