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

By Christopher Tong (Eds.)

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

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Design case storage. In BOGART, the cases were automatically stored ver­ batim (when the user so chose) after a session with the VEXED design system (Volume I, Chapter 8). In ARGO, the design plan (a network of design steps and dependencies among them) is partitioned into levels. By dropping away more levels, more general plans are produced. Explanation-based generalization [19] of these design plans is used to determine the conditions under which each of these plans is applicable (which are then cached, along with the correspond­ ing plans).

This kind of design process model is demonstrated in several systems discussed in this book, including AIRCYL (Volume I, Chapter 7) and VEXED (Volume I, Chapter 8). */, where p is the number of parts in the original specification, and / is the number of levels of abstraction through which each such part must be refined. However, constraint processing can slow things down, particularly if relatively global constraints are being processed [13]. 4. ) are involved, but several (but not an exponential number of) iterations are generally required before an acceptable design is found.

3. Negotiation techniques, which deal with conflict detection and resolution between various agents. 4. Transaction management issues, which deal with the interaction issues between the agents and the central communication medium. 5. Design methods, which deal with techniques utilized by in­ dividual agents. 6. Visualization techniques, which include user interfaces and physical modeling techniques. Several papers in Volume ΠΙ address some of the above issues; [33] contains ad­ ditional papers in this area.

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