We demonstrate how the use of logic models and approximate reasoning can lead to more effective conceptual design of a large-scale scientific/industrial complex. A deductive model is used to describe the relationships between the mission of a complex, the tasks that are the concrete expressions of the mission, and the capabilities and resources that allow the mission to be carried out. This deductive logic model provides the formal basis for integrating these relationships into a conceptual design and provides a framework to express design options that are an essential part of the description of the complex. A decision model for choosing among the design options is constructed using approximate reasoning. This AR model uses forward-chaining inference models to emulate the types of reasoning used by experts. This approach allows the analyst to use both numerical data when available and the qualitative knowledge that forms much of the information base used in conceptual designs of new and innovative complexes.

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