ML Anthology

Learning Design Guidelines by Theory Refinement

Jacob Eisenstein
AAAI 1999 pp. 960
/aaai/1999/eisenstein1999aaai-learning/

Abstract

The automation of design decisions can be seen as a problem of generating mappings between elements in an abstract specification of the object to be designed and the concrete parts of the object itself (Puerta and Eisenstein 1999). In some cases, it is difficult to discover a formalism that takes all relevant variables into account; human designers proceed by Òintuition.Ó Individual designers may have stylistic preferences that are purely idiosyncratic or are common only to one particular Òschool.Ó By ignoring such preferences, automatic design forfeits the flexibility, creativity, and vitality of human design. In short, automatic design algorithms suffer from a lack of flexibility. Adaptation is offered as a solution to this problem. By making automatic design algorithms adaptive, we can begin to do automation without a complete

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Text

Eisenstein. "Learning Design Guidelines by Theory Refinement." AAAI Conference on Artificial Intelligence, 1999.

Markdown

[Eisenstein. "Learning Design Guidelines by Theory Refinement." AAAI Conference on Artificial Intelligence, 1999.](https://mlanthology.org/aaai/1999/eisenstein1999aaai-learning/)

BibTeX

@inproceedings{eisenstein1999aaai-learning,
  title     = {{Learning Design Guidelines by Theory Refinement}},
  author    = {Eisenstein, Jacob},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1999},
  pages     = {960},
  url       = {https://mlanthology.org/aaai/1999/eisenstein1999aaai-learning/}
}