With the large set of existing books related to modeling and simulation, it would be easy to dismiss this text as having little new to offer. The motivation for Birta and Arbez is to provide a foundational education in modeling and simulation, which separates it from many domain-specific alternatives. The book is ultimately successful as an approachable, general, yet nontrivial introduction to the broad field of modeling and simulation.
From the outset, Birta and Arbez make clear their intent to provide a solid foundation for an introduction to the diverse and growing field of modeling and simulation. They claim no particular bias in their approach, and, indeed, the book is largely agnostic with respect to methodology and domain. There is a notable emphasis on discrete event modeling over continuous time. In all fairness, however, the basics of continuous time modeling are the subject of countless quality texts in mathematical and numerical analysis.
One might argue that a text that is so broad and attempts to cover such a wide range of topics would be superficial and of limited utility—I believe otherwise. Indeed, as we see the field of modeling and simulation mature, we will increasingly see the need for introductory courses that can be used as a springboard into deeper, more specialized approaches. This text serves that purpose well, although I am eager to see the second edition address certain frailties. If modeling and simulation continue to develop, as some predict, into a recognized discipline, then its practitioners will need to formulate a recognized, common, domain-independent set of tools and skills. This book is clearly aimed toward that end. Its only limitation is that it largely discounts “experiential” simulations (such as simulators and virtual environments) in favor of experimental and analytical intent. Interestingly, it notes the modern genesis of modeling and simulation to be coincident with early Link trainers. I am sure that many in the field would argue that modeling and simulation have been around almost as long as language itself, but that is more of a philosophical distinction than a technical one.
The book is organized logically into parts dealing with foundations, the discrete-event paradigm, and the continuous-time paradigm. This flows fairly naturally, with continuity maintained through the development of increasingly sophisticated models as the lessons unfold.
The first section is perhaps the most unique, as compared to other modeling and simulation texts. It provides a substantial mathematical foundation. It also provides a well-rounded formulation of the simulation development process, without being prescriptive or formulaic. This is a noteworthy achievement, as it would have been considerably easier to simply adopt a methodology and provide a cookbook. That tactic would have been less than general, and, therefore, not consistent with the overall goals of the introduction. The first section emphasizes the “conceptual model of modeling and simulation.” Birta and Arbez dive right into the core concepts of abstractions, context, and the definition of the system under investigation. The detail in which these concepts are covered borders on philosophical. However, rather than it being a digression or distraction, these concepts actually serve to homogenize ideas that transcend methodologies and—within the book—the discrete and continuous paradigms. Some experts in the field may not agree with some of the terminology or specific concepts presented, but this should not detract from the overall effectiveness of introducing these foundations at such an early stage of modeling and simulation education.
The second section deals with discrete event simulation (DES) paradigms and constructing complete simulation systems using DES methods. The approach taken by the authors is claimed to be novel, but their activity-based construction is relatively common among practitioners. The authors mention, but are somewhat dismissive of, other approaches, such as Petri nets and discrete event system specification (DEVS), as not sufficiently general. This is unfortunate, as the approach taken in the book stands very well on its own, and would be useful as a stepping stone to more narrowly focused approaches. One would hope that a subsequent edition would describe an even larger number of alternatives, offering up rationales about what aspects of a simulation would make one approach preferable over another.
One noteworthy difference between this and other general modeling and simulation texts is the way in which certain areas, heretofore considered advanced topics, are introduced. For example, the topic of random number generation is covered very early on in the development of the discrete event modeling paradigm. By taking this approach, the authors provide these topics as tools rather than mysterious, and somewhat separate, areas of research. The outcome may be a more consistent and holistic approach to the introduction of the modeling and simulation discipline. Certainly, it provides an understanding of the utility of these specialized areas, while motivating the need for additional research where warranted.
The third section deals with continuous time approaches. Overall, this section suffers from being a bit thin. The section describes the paradigm fairly well, and does a nice job of contrasting it with the discrete-event paradigm. The reader is quickly guided through some basic mathematics and into a couple of nicely formed problems. The simple examples used do not provide enough explanation of how mathematical expressions are translated into code. Separation of the mathematical model from the mechanics of the ordinary differential equation (ODE) solver can be a difficult concept to comprehend. Instructors using this text to introduce computational techniques might find the need to supplement the examples provided.
Introducing continuous-time dynamic systems, the rapid transition from motivation through mathematical primitives to ODE solvers does not flow as nicely as the discrete event section. Furthermore, the authors are restrictive in their refinement of the domain into two essential problems, initial value and steady state, as to be unsatisfying to a general computational scientist. While it would be too much to try to cover the entire spectrum of numerical methods and computational techniques, the continuous-time paradigm should provide a general foundation for understanding the field of computational sciences, including difficult problems that motivate current topics in high-performance computing. The flow of this section may lead one to believe that the authors simply ran out of time before giving this section the attention it deserves. Readers can hope that this will be remedied in the next edition.
In this first-edition textbook on modeling and simulation, Birta and Arbez have created a well-rounded, general introduction to a very difficult field to enter. The text fills a clear gap in the resources available for introducing this field. The holistic, neutral treatment of a wide variety of topics provides an alternative to the typical modeling and simulation survey course, which tends to be assembled from a hodgepodge of domain-specific examples. While there may be some parochial arguments with some of the terminology, the overall utility of this text seems clear. The material provided seems to be appropriate for an upper-division undergraduate course leading to a concentration in modeling and simulation. It would be equally well suited as a first course in modeling and simulation at the graduate level, as a primer for advanced-simulation topics in the context of computational sciences or high-performance computing.
This text will not satisfy those looking for a domain-specific modeling or simulation technique, or for a lead-in to some specific advanced area. The material presented is intentionally domain neutral, save for the obvious requirements of the concrete examples. The text might also be unappealing to those seeking a prescriptive life cycle or development methodology. The concepts presented should apply equally well to any number of methodologies, but do not attempt to constrain either the modeling or software-development methodologies.
Overall, the authors have succeeded in creating a broad, balanced perspective of the modeling and simulation discipline. Readers will gain a refreshingly unified understanding of how simulation springs from conceptual models and context, regardless of domain or application.
