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The main features of the System Entity Structure, its specializations and aspects, as well as pruning and model generation have now been introduced. Such concepts provide a wealth and variety of potential hierarchical structures with which to tackle complex Systems of Systems problems. However, the rapidly growing combinatorial spaces that are set up by specialization and aspect selections can outstrip human capacity to do manual pruning. Accordingly, this chapter discusses automated pruning—concepts and tools for pruning that can reduce, and sometimes, eliminate, the manual pruning that is otherwise required. Enumerative pruning entirely eliminates manual pruning entirely but is restricted to small enough solution spaces. Random pruning samples from a large solution space to give a statistical picture of the space. Context free and context sensitive selection rules provide the ability to constrain the solution space to combinations that are more likely to meet your requirements.
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Zeigler, B. P., & Hammonds, P. (2007). Modeling&simulation-based data engineering: introducing pragmatics into ontologies for net-centric information exchange. Boston: Academic Press. 448 pages.
Zeigler, B. P., Kim, T. G., & Praehofer, H. (2000). Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems (2nd ed.). Boston: Academic Press.
- Automated and Rule-Based Pruning
Bernard P. Zeigler
Hessam S. Sarjoughian
- Springer London