Critique: Compiling Design Plans from Descriptions of Artifacts and
Problem-Solving Heuristics
Araya, Mittal
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While a reasonable justification is given for making an analogy between
knowledge compilation and computer language compilation, it would
have been nice to see acknowledgment of the opposing opinion that
the two have very little in common. One alternate point of view is that
knowledge compilation often takes a very specific, all encompassing
source of knowledge and extracts the pieces that only pertain to a
certain task, often abstracting the knowledge so it applies to a
set of problems. Computer language compilation on the other hand takes
a high level language and translates it into a very specific, exact
representation for use on a particular platform. Also, the problems
solved or tasks carried out by the compiled program are no different
from those intended by the higher level representation.
It was interesting to see that a common aspect of design systems that
incorporate learning is the profuse use of cross-indexing various
pieces of information in the representation. One example is Keller's
compiling redesign plans work where all quantities kept a list of
equations they appeared in. This is analogous to the theory of human
intelligence that suggests much of the information processing
capability and creativity the people exhibit is largely a function of
the presence of a highly connected memory system. Creating connections
between different pieces of knowledge is a form of learning or
discovery. It is no surprise that machine learning systems tend to
have more indexing than non-learning systems.
I am not completely convinced that a distinction must be made between
"always-relevant" parameters and "possibly-relevant" parameters.
It seems to complicate the system more than it is worth. Since
always-relevant parameters are simply those that are used to specify
constraints on the functionality of the thing to be designed, they would
be easily identified at run time.
I thought it odd that with the capability of generating design plans
automatically there was no mention of a method for choosing a design
plan automatically given a new problem. Is the system simply going
to generate a new plan for every new problem? I don't think so. With
the automation of design plan creation, one would expect there to be
many more design plans to choose from.
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Agustin A. Araya & Sanjay Mittal,
Compiling Design Plans from Descriptions of Artifacts and
Problem-Solving Heuristics.
Proc. Int. Jnt. Conf. on AI, IJCAI-87, 1987, pp. 552-558.
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