expose, but that cannot be exposed by the individual systems themselves. The immersive visualization of results, including detection and visualization of new emergent behaviors, is a pivotal role for the simulation. In other words, simulation can take over the role of secondary players, opposing forces, and supporting roles in planning and preparation, while also supporting computational and visualization requirements in execution and evaluation.
However, the use of modeling and simulation is not limited to the execution phase but can be applied by the operations group in support of many of their tasks. During the design and the development of the wargame, tools can help to visualize ideas and support the composition and reuse of services and rules developed in earlier wargames. Quick consistency checks can make sure that all entities necessary to evaluate a new idea are represented, and all of them have rules assigned that can help with the necessary scenario generation process. For rehearsing, artificial intelligence can be used to calibrate software agents and rules to play the role of human gamers to look for inconsistencies, opportunities to cheat, and other optimization of actions. It may be premature to think about artificial gamers as subject matter experts, but for the pure testing of the limits of the game, current technologies are sufficient. Communicating the results of the wargame is also a task well known by the simulation community, as in the domains of analysis and training providing after action reviews (AAR) has been required for many years. If done correctly, results and lessons learned can inform the development of new rules for the next events. A picture says more than a thousand words, but an executable simulation can say more than a thousand pictures. Scenario generation tools and other support software should also be utilized in this context.
There are several challenges that simulations for defense operations must overcome to be fully supportive of today’s requirements. Nonetheless, the increasing complexity of the highly nonlinear operational environment needs such computational support. The recently published primer on complexity for systems engineers, developed and published by the International Council on Systems Engineering (INCOSE), explicitly mentions simulation and artificial intelligence methods as necessary tools for decision‐makers in such environments, as complexity requires a new operational agility from the decision‐makers, which means to rapidly compose high‐performance teams out of the available systems to react quickly and precisely to often unforeseen, maybe even emergent challenges.
Simulation solutions provided for defense are reasonably effective in the modeling of physical and kinetic effects, such as needed for attrition‐focused force‐on‐force modeling. However, the structure of the opposing forces is changing rapidly, driven by increased use of robotic systems and other autonomous systems that lead to new tactics and procedures. New weapon systems, such as the 5th‐and 6th‐generation systems, provide a new set of capabilities. Opposing systems and future systems are hard to capture, as the parameters – or even the underlying architecture – are unknown or uncertain. Many lessons learned are no longer applicable.
How and where we will have to solve future conflicts is not only challenged by more than such technical uncertainties. With more and more people moving toward mega‐cities, many of them in coastal regions, the likelihood of an armed conflict in these regions increases. This will require high‐resolution modeling of this environment with high fidelity on a big scale. This will require sensor and weapon system models with equal resolution and fidelity, and the adaptation of rule sets on how to apply these systems, for all participating organizations. International multidomain operations require a new level of coordination between the systems of various services and nations as well as the local commanders utilizing their capabilities. These new kinds of operations are more than joint and combined activities, they are the creative mix of several mission threads optimally creating mutually supportive effects in all domains.
Furthermore, human, cultural, and social behavior modeling will be needed, which implies the use of computational social science models for both opposing and friendly forces. With the advancement of combat medicine saving more soldiers, new challenges emerged, like having to deal with post‐traumatic stress syndrome (PTSD). The use of information, including social media, to influence opponents, disseminate information in support of the objective of the organization, and other nontraditional intelligence operations may influence future warfare as well.
The traditional use of predictive simulations used for point optimizations in a well‐defined context, possibly supported by some sensitivity analysis, does not meet these emerging requirements. Composable simulation services provided as smart components are needed. The resulting compositions need to be applied to conduct exploratory modeling and analysis addressing the deep uncertainties of these complex environments by allowing a broad evaluation of the solution space. By combining the power of computer simulation‐based generation of data with technology of big data allows for a new application of simulation.
In summary, modeling, simulation, analysis, and visualization methods can and should enrich wargaming activities. No other methods allow the exploitation of options within a complex, nonlinear environment, such as the modern battlefield presents. Several chapters in this book provide examples of how these methods and derived tools help in the decision‐making process. Not utilizing these methods and tools to the full extent possible would be a mistake.
A Wargamer’s Perspective
Recent DoD level interest has highlighted the importance and value of wargaming as a vital and neglected element in the comprehensive understanding of operational environments, force design, and operating concepts. There is both clarity and confusion in this interest. Clarity in that it recognizes a problem and gives momentum to a solution; confusion in that it has not distinguished between the natures of computational analysis and wargaming. It has even suggested that “reinvigorating” wargaming is merely a matter of incorporating analytical techniques (methods, models, and tools – MMT) into wargame designs. However, the effort to optimize this relationship entails more than the simple incorporation of MMT into wargame design. This incorporation is not new. The struggle is to synchronize the process of sophisticated analytical methodologies with the action of the human intellect such that the potential of both are integrated and optimized by using the computational result as a substrate for human decision.
Analysis is based upon mathematical process; wargaming is based upon human judgement. Both are powerful and are compatible. But, they are not different expressions of the same thing. Computational analysis relies for its manipulation of data and its precision of results upon a methodology involving the quantification of variables and the specification of their interactions. In analysis, exact conclusions emerge from the connection of method to a specific problem. However, analysis is limited by the very tenants of its science to what is measurable. It cannot go beyond statements of trends and precision (accuracy is another matter) because it cannot substantiate what it cannot measure. Further, a particular resulting measurement does not necessarily imply a universal pattern.
Wargaming rests upon what cannot be measured. This stands in contrast to but not in opposition to the computational analytical approach. A wargame does this by embracing, assembling, and organizing many variables without an attempt to assign values or calculate interactions. These variables, which reside in the situation, the individual, and emerge in the dynamic friction of play, are impossible to measure separately or in assembly. The action of the wargame generates interactions and relationships that could not have been anticipated and relies upon the emergence of results not subject to prediction. All of this is synthesized and organized in the human imagination and no science is capable of quantifying the path, dynamic, or chance that transforms this complexity into a comprehensible and coherent whole. And yet this is what both drives a game and defines its results.
Thus, wargames explore the interlocking coherence of the whole while computational analysis produces precision in isolation. The question is: How to associate the two to mutual benefit? The problem is one of relating processed facts and human imagination. The analyst and the wargame designer must combine the two realms without losing the essential strength of either in the midst of the constant dynamic and change in game play. The answer to this dilemma involves the recognition of the distinct natures of the two approaches and the effort to forge complimentary methods. Wargaming permits judgment to be influenced in a