User talk:Ancheta Wis/a

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[edit] knowledge representation

[edit] Remarks on the History section

The history section is kind of longish and expecially the beginning is too far fetched. In many fields of study people have a tendency to extend the history of a field beyond the actual beginning. Of course one can say that DNA is way to represent knowledge. However most of the interesting things how this is done are not know (yet). So it does not actually give a good account of what people think what knowledge represenation is. It is a term which has the roots in the context of data analysis and general computing and it probably about 20..30 years old. Who has some more details on the first uses of the term?

I propose to just delete the first three paragaphs.

The history of KR can be said to begin with DNA and memory molecules,...

Mathematics and related logical notations such as predicate ....the Big Bang ...

In philosophy knowledge is most commonly defined as "justified true belief". Hirzel 13:21, 20 October 2005 (UTC)


As there was no reaction yet I think I may move the three paragraphs to here for the time beeing. Hirzel 23:24, 6 November 2005 (UTC)
The history of KR can be said to begin with DNA and memory molecules, which represent information about how to construct various organisms. This may be considered a knowledge representation. Spoken and written language also represent knowledge. The sum total of all books used to pass knowledge from one generation to the next amount to an extensive KR, with the pace of change increasing exponentially since perhaps 1600.
Mathematics and related logical notations such as predicate calculus are more formal and precise representations used for certain kinds of knowledge. Computer models and simulations also amount to representations of knowledge, from the Big Bang to society and culture.
In philosophy knowledge is most commonly defined as "justified true belief". However, knowledge representation uses the term much more broadly: there need be no belief for DNA to function, and language can easily represent incorrect beliefs, as well as things not believed at all.
Hirzel, thank you for your interest in this article. Clearly, the history of the subject stems from the AI days, which waned in the late '80s and which has become part of the stable infrastructure of the field, when it became clear just how difficult the problem of KR is. You can look in the AI books of the period (Nilsson, Winston, etc) to find a sentence whose canonical statement is something like If we can just choose the right representation for the problem at hand, then it becomes easy to solve. But then we have the issue of translating the solved result back into some other representation which some other field can apply. So transformation of the representation becomes the bottleneck; it is akin to the differences in cultures between societies, with turf and priority etc. But if we just ignore this problem what have we got? We have something like the invariants of physics, something which remains unchanged by the transformation from one representation to another. So then we have to state conditions, axioms, transformation rules, a whole calculus. This is doable. Next the problem is to somehow summarize these solved results so that they are not just islands of information, but are pregnant with meaning somehow. We have analogies with the specific interests of a society, or a community of researchers, or businesses, which have hot issues with which they are concerned. What we have found is that the specific point solutions which the published programs have solved can each be generalized into their shells, like Mycin etc. That is where we sit. We have this 1980s knowledge which embodies specific algorithms. We have the newer easier-to-use languages which go beyond the limitations of the specific languages. We have representations like HTML or XML which are tuned to the uses like Browsers or Web Services. We have robots which talk to satellites to win their autonomous vehicle road races.


== Mechanical operation == addiator Use the image at the right to follow the discussion.

Quantity is denoted by length. Positive numbers are represented in the upper tracks of the addiator. Negative numbers are represented in the lower tracks of the addiator. In the version shown, the two rightmost tracks can represent values to the right of the decimal point. Thus this version can represent quantities up to 9,999.99 .

The register, or accumulator displays its state in the series of holes in the center of the calculator. To clear the register to zero, pull upward on the bar at the top, which aligns the linear cogs to zero.

Addition takes downward motion of the stylus, whose point is inserted into the hole at each of the columns which correspond to the digit at the left or right of the decimal point. If carry is required, the track for the decimal column takes a turn into the next decimal column, which the stylus simply follows. (See the semicircular track at the top or bottom of each decimal column.)

Subtraction takes upward motion of the stylus. If borrow is required, the stylus simply follows the semicircular track in the decimal column.