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Defense Modeling, Simulation, and Analysis: Meeting the Challenge
not well understood, and existing knowledge about phenomena such as terrorism or counterinsurgency has not been fully codified into models. Accordingly, models and analysis of networks and of complex adaptive systems, along with the use of embedded M&S, are central drivers for the development of future MS&A tools. The way that the defense MS&A enterprise should respond to these developments— the emergence of networks, adaptive systems, and embedded systems—forms the central theme of this report.
Chapter 3 identifies high-leverage opportunities for MS&A research needed to address the expanded mission space. Such research would expand the science foundation of MS&A. Building on a list of the new capabilities needed for the MS&A enterprise, the chapter discusses promising approaches for obtaining them, emphasizing the mathematical, scientific, and computational advances that have not yet been sufficiently incorporated into modeling technology and new topics where research can have a disproportionately large payoff.
The committee concluded that four main objectives should guide DoD’s MS&A efforts, and it developed the following four general recommendations:
Recommendation 1: DoD should give priority to developing flexible, adaptive, and robust MS&A methods forevaluating military strategies.
Recommendation 2: DoD should ensure that the basicarchitecture of its MS&A systems reflects modern concepts of network-centric warfare.
Recommendation 3: DoD should give special emphasis tothe development of MS&A capabilities that are neededwithin embedded systems.
Recommendation 4: DoD should establish a comprehensive and systematic approach for developing the MS&Acapabilities to represent network-centric operations:
Enhance and sustain collaborations among thevarious parties developing network-centric MS&Acapabilities.
Continue and extend the development of existingapproaches to modeling network-centric operation.
Establish a new mathematical basis for models describing network-centric operation, drawing on anarray of approaches, particularly complex, adaptive systems research.
The diversity of challenges facing the DoD MS&A community requires a diversity of mathematical and modeling approaches, and the committee recommends that this be embraced as a guiding principle.
Recommendation 5: DoD’s analytical organizationsshould take a portfolio approach to designing their analyses and supporting research, investing in a range of methods including diverse models, games, field experiments,and other ways to obtain information.
In Chapter 3, the committee goes on to develop four more recommendations related to particular technical directions identified in the chapter:
Recommendation 6: DoD should devote significant research to social behavioral networks and multiagent systems because both are promising approaches to the difficult modeling challenges it faces.
Recommendation 7: DoD should form a research centeror consortium focused on game-based training and simulation.
This report highlights the ubiquity of network-centricity for future DoD operations, but there is little scientific foundation for DoD networks or for those that appear elsewhere throughout our society. The committee believes that such foundational research would redound to the benefit of DoD.
Recommendation 8: DoD should support and extend initiatives to cooperate with other agencies funding researchon networks.
Recommendation 9: DoD should begin cooperative programs of research into embedded systems with otheragencies facing similar demands.
In Chapter 4 the committee presents approaches for improving the interface between MS&A practitioners and decision makers and makes two related recommendations. This interface presents a perennial challenge, not just in DoD, but in every situation where the results of sophisticated and nuanced MS&A must be condensed and conveyed, at appropriate but variable levels of detail, to end users. As DoD plans for its expanded mission space in the face of increased uncertainties, it is critical that the best MS&A be used and used effectively, because novel missions and increased uncertainties lessen the ability of decision makers to rely solely on their collected experience and judgment. Good professional practices are identified for translating a decision problem into an MS&A study that will assist in making that decision and for facilitating appropriate interaction with the decision maker. Emphasis is put on the communication skills needed to frame results accurately, including representation of the many levels of uncertainty inherent in any such solution.
There is a fundamental need for better understanding of the cognitive styles of decision makers and their interaction with different forms of MS&A. For instance, much is unknown about how information is absorbed and what biases might be introduced by alternative means of presentation. Research into the different cognitive styles of decision mak-