Artificial Intelligence in Engineering Design. Models of by Christopher Tong (Eds.)

By Christopher Tong (Eds.)

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Additional info for Artificial Intelligence in Engineering Design. Models of Innovative Design, Reasoning about Physical Systems, and Reasoning about Geometry

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The DIOGENES compiler [24] addresses the still broader class of heuristic search algorithms. These compilers appear to obey the standard power/generality tradeoff. , relatively unrestricted) models as: a transformational model of knowledge compilation [22] or a model of knowledge compilation as formal derivation. All the compilers just mentioned are research prototypes, and are thus not commercially available. Nonetheless, we mention this technology because of its potential importance in the not too distant future.

Then the unspecified structure would be the values for all the remaining parameters. Gap in abstraction levels between specification and implementation. In the simplest case, the design specification and the design implementation are at the same level of abstraction. This occurs, for example, when the only unspecified structure is parameter values. In other cases, a single level separates the func­ tional specification from the target implementation level. That is, knowledge and methods are available for directly mapping the pieces of the specification into implementations; implementing a boolean function as a gate network is a simple example.

Two major types of design interactions are worth distinguishing. Compositional interactions arise when not all choice combinations (for refining or implementing the different parts of the design) are (syntactically) composable. For example, in VLSI design, the output of one part may be "serial”, while the input of another may be "parallel”; if the output of the one must feed the in­ put of the other, then the parts are not syntactically composable. , in VLSI design, wirel and wire3 on the chip must be at least 3 lambda units apart).

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