paradigms. DOD has many manufacturing processes and similar processes, such as logistics repair, that could significantly benefit from agile or flexible design based on discrete event simulation.

Dynamic Structure Modeling and Simulation

In many important physical and military systems, the system “structure” changes in the course of time. For example, biological systems such as growing plants, and social systems such as self-organizing organizations (one model for highly dispersed ground forces in the future), change structures over time. So also does a military organization that suffers attrition and reorganizes with a new command structure or a military organization that reorganizes and replans because of events making the original concept of operations obsolete.

Although significant research has been done on such simulations, current simulation languages do not support them. To represent such changes, they must be recast into parameter changes, and this leads to convoluted code that is difficult to verify and inefficient to run. Augmenting or replacing current simulation languages to support dynamic structure modeling would greatly increase the power of simulations to study complex structurally variable systems to gain true insight and predictability. This technology has been the subject of numerous investigations, but only recently has a first theoretical framework even been proposed and implemented. Thus, research that can contribute to a coherent usable methodology is at an early phase. 1

Inductive Modeling

Inductive modeling attempts to infer a system's internal structure from data representing its behavior. Given that data collected from all kinds of systems are abundant, realizing a comprehensive inductive modeling methodology will be of significant importance to the M&S community at large. Within the military domain, it may be possible to generate rich databases from exercises and training activities mediated by distributed interactive simulations.

Despite a large body of research in inductive modeling, there is little agreement on any recognized inductive modeling paradigm. Several software implementations exist, including one developed based on a well-defined framework for inductive modeling, and implemented in a Artificial Intelligence Truth Maintenance system supporting nonmonotonic reasoning (Sarjoughian, 1995). This type of reasoning is needed to support flexible assertion and retraction of abstractions and assumptions in model building. However, this work has only tackled

1  

One example of work in this domain involves support to DOD's business reengineering, which must reflect the self-organizing formation of teams in business structures.



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