Defining Simulation

What is Modeling and Simulation (M&S)? While M&S as a field is seen as one entity, it is actually composed of two interdependent concepts: modeling and simulation (Birta, 2003). In this series I present various pre-existing definitions of these three terms to discuss the common themes and solidify the meaning of each.

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Simulation

Many people use “simulation” as a catch-all phrase. Some incorrectly use “simulation” to mean “model” and some use it incorrectly to mean “M&S.” The difficulty in defining simulation is that there are many different uses of simulation; for example, Ören (2014), lists over 500 types of simulation in his publication. At the highest, most abstract, level all types of simulation are the same across all domains and application areas, however, there are some variations of the definition based on its intended use.

https://www.youtube.com/watch?v=cBxYEq7-RsM

I compiled a list of definitions for “simulation” throughout M&S literature. The intent here was not to create an exhaustive list, but to demonstrate the number of definitions available and the commonalities and differences in definitions. I present this list alphabetically by the last name of first author for each source.

Common Themes across Definitions of Simulation

The first noticeable theme is the use of a model as a foundation. The representation of something is used and then M&S professionals look at this model over-time and/or in multiple states. Time is a common theme in simulation. It is what sets the simulation apart from the model itself. However, some sources do not properly account for the temporal component of simulation. Ören, (2005) presents a definition from Intermath (“Simulation,” 2005) definition to demonstrate a point – the definition is incorrect; because, the phrase “[a]n experiment that models a real-life situation,” does not necessarily capture the notion that one investigates the model’s state over time. This definition also does not account for varying states. The element of multiple varying states is an important and often overlooked theme of simulation. A simulation should vary in state, otherwise it would remain a model. Thus, the simulation should demonstrate the dynamic nature of the model when changing parameters/variables.

Differences in Definitions of Simulation

At a high-level, one definition should be generalizable across all types of simulation, but the differences in definitions are due to either the source or the context of the simulation. Specifically, (Ören, 2014) breaks up simulation into two main categories: Simulation for Experimentation and Simulation for Experience. This is the most contemporary understanding of “simulation” presented by Ören (2011b); however, this is not the only understanding Ören (2011b) presents. You have seen these definitions in the above table, but I am reproducing them here for readability. Simulation for Experimentation is “goal-directed experimentation with dynamic models” whereas Simulation for Experience is “providing experience under controlled conditions for training or for entertainment,” (Ören, 2014). Ören (2014), further breaks down Simulation for Experience into Simulation for Training and Simulation for Amusement. Simulation for Training is “providing experience under controlled conditions for gaining/enhancing competence in one of the three types of skills: (1) motor skills (by virtual simulations), (2) decision and/or communication skills (by constructive simulations; serious games), and (3) operational skills (by live simulations),” whereas Simulation for Amusement is “providing experience for entertainment purpose (gaming simulations),” (Ören, 2014). When I discuss this with others I often interchange this phrase for "simulation for entertainment." These variations should be used to distinguish different types of simulation but should still include the notion of using a foundational model and temporal elements/varying states, which is not evident in the Ören definitions when taken out of context.

It is important to note that while some (Birta, 2003) insinuate that simulation is executed using only hardware and software, this is not always the case; for example, within the Live, Virtual, and Constructive Simulation Paradigm, Live simulation does not require computing power. Even though (Birta, 2003), mentions this sentiment, his definition still leaves out a large portion of what simulation includes. This practice is common, especially amongst journals and conferences focused on engineering and computer science aspects of M&S, but this assumption is not always clearly stated, which can, at best, confuse and, at worst, bias or misinform novice readers. Simulation existed pre-computer era (L. Bair & Jackson, 2013), and this should be considered when determining or developing a high-level definition of simulation that applies to all types.

Based on this, the definition of simulation should be “a method for implementing a dynamic model over time,” (adapted from Ören, 2005; and Ören, 2011b).

Ören (2011b) and Pritsker (1979) delve into the background, themes, inconsistencies, and misuse for the word “simulation” in greater depth than presented here. To explore these definitions deeper would be outside of the scope of this post, but the opportunity to do so may be relevant for future work in determining M&S education standards.

I would love to read your thoughts on the term simulation. What do you think the operational definition should be?

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References

Bair, L., & Jackson, J. J. (2013). M&S Professionals Domains, Skills, Knowledge, and Applications. Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), Orlando, FL. http://iitsec.ndia.org/about/PublicationsProceedings/Documents/BP_HSE_13313_Paper.pdf

Birta, L. G. (2003, February 19). The Quest for the Modelling and Simulation Body of Knowledge. The Sixth Conference on Computer Simulation and Industry Application, Instituto Technologico de Tijuana, Mexico.

Bungartz, H.-J., Zimmer, S., Buchholz, M., & Pflüger, D. (2014). Modeling and Simulation. Springer Berlin Heidelberg. http://link.springer.com/10.1007/978-3-642-39524-6

Ören, T. (2011). A Critical Review of Definitions and About 400 Types of Modeling and Simulation. SCS M&S Magazine, July, 142–151.

Ören, T. (2014). The Richness of Modeling and Simulation and an Index of Its Body of Knowledge. In M. S. Obaidat, J. Filipe, J. Kacprzyk, & N. Pina (Eds.), Simulation and Modeling Methodologies, Technologies and Applications (Vol. 256, pp. 3–24). Springer International Publishing. http://link.springer.com/10.1007/978-3-319-03581-9_1

Ören, T. (2005). Toward the body of knowledge of modeling and simulation. Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), 1–19.

Ören, T., & Waite, B. (2010). Modeling and Simulation Body of Knowledge Index: An Invitation for the Final Phases of its Preparation. SCS M&S Magazine, October(4). https://www.researchgate.net/profile/Tuncer_Oeren/publication/228749480_Modeling_and_Simulation_Body_of_Knowledge_Index_An_Invitation_for_the_Final_Phases_of_its_Preparation/links/0c960530f882e26424000000.pdf

Pritsker, A. A. B. (1979). Compilation of definitions of simulation. Simulation, 33(2), 61–63.

Rogers, R. V. (1997). What makes a modeling and simulation professional?: The consensus view from one workshop. 1375–1382.

Salas, E., Wildman, J. L., & Piccolo, R. F. (2009). Using simulation-based training to enhance management education. Cademy of Management Learning & Education, 8(4), 559–573.

Sokolowski, J. A., & Banks, C. M. (2009). Principles of Modeling and Simulation: A Multidisciplinary Approach. Wiley.