Bhatta, S. R. & A. K. Goel (1997). Design patterns: A computational theory of analogical design. In the Proceedings of IJCAI-97 workshop on "Using Abstraction and Reformulation in Analogy."

@InProceedings{Bhatta97,
  author = 	 {Sambasiva R. Bhatta and Ashok K. Goel},
  title = 	 {Design Patterns: {A} Computational Theory of
                  Analogical Design},
  booktitle = 	 {Proceedings of IJCAI-97, workshop on Using
abstraction and reformulation in analogy},
}

Author of the summary: Jim Davies, 1999, jim@jimdavies.org

Cite this paper for:

• design patterns: Specify generic relations among abstract design elements.
• System: IDEAL
• Generic Teleological Mechanisms (GST): specify generic functional relations and abstract causal structure of a class of devices.
• Model-based Analogy (MBA): a normative theory of analogical design that provides a process account of acquisution, access and use of Generic Teleological Mechanisms (GST).
• "..design patterns are what gets learned from one design situation and transferred to another situation."
• IDEAL evaluates a candidate design by qualitative simulation.

The input of MBA is a set of structural constraints and functional requirements. Output is a structure that satisfies those constraints.

Design analogues are indexed in memory by both the functions that the stored designs deliver and by the structural constraints they satisfy.

A perfect match if input and output states, and property values and their constraints are identical.

If nothing exact is found, then IDEAL retrieves something close and transforms it. GTMs provide knowledge that allows for encapsulation of relationships between modifications and their causal effects. It then uses qualitative simulation to evaluate the transformed designs.

IDEAL evaluates a candidate design by qualitative simulation.

This is how IDEAL works:

Start with problem constraints.

RETRIEVE m1, a model from memory.
---------------------------------
  - retrieve the best model you can based on constraints.
  - if that isn't the solution to the problem then go on.

GET m2, the solution to the problem.
------------------------------------
  - try modifications
     - use differences between m1 and abstraction of problem
       constraints to get GTM
     - instantiate
     - compose behaviors
     - evaluate (using qualitative simulation)
  - if that fails then have oracle give correct answer m2.

GENERALIZATION
--------------
  - do solution abstraction	
  - save as a GTM what about m2 made it better than m1

Design Patterns

Learning GTMs

Summary author's notes:

• none