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BP508 Bongard Problems with precise definitions vs. Bongard Problems with vague definitions.
BP1
BP3
BP4
BP6
BP13
BP23
BP31
BP67
BP72
BP103
BP104
BP210
BP292
BP312
BP321
BP322
BP324
BP325
BP329
BP334
BP344
BP348
BP367
BP368
BP376
BP384
BP386
BP389
BP390
BP391
BP523
BP527
BP557
BP558
BP559

. . .

BP2
BP9
BP10
BP11
BP12
BP14
BP62
BP119
BP148
BP364
BP393
BP505
BP508
BP509
BP511
BP524
BP571
BP812
BP813
BP847
BP865
BP894
BP895
BP939
BP1002
BP1111
BP1158
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COMMENTS

Bongard Problems sorted left have the keyword "precise" on the OEBP.

Bongard Problems sorted right have the keyword "fuzzy" on the OEBP.


In an precise Bongard Problem, any relevant example is either clearly sorted left, clearly sorted right, or clearly not sorted.

(All relevant examples clearly sorted either left or right is the keyword allsorted.)


How can it be decided whether or not a rule is precise? How can it be decided whether or not a rule classifies all "examples that are relevant"? There needs to be another rule to determine which examples the original rule intends to sort. Bongard Problems by design communicate ideas without fixing that context ahead of time. The label "precise" can only mean a Bongard Problem's rule seems precise to people who see it. (This "precise vs. fuzzy" Bongard Problem is fuzzy.)


In an precise "less than ___ vs. greater than ___" Bongard Problem (keyword spectrum), the division between the sides is usually an apparent threshold. For example, there is an intuitive threshold between acute and obtuse angles (see e.g. BP292).


As a rule of thumb, do not consider imperfections of hand drawn images (keyword ignoreimperfections) when deciding whether a Bongard Problem is precise or fuzzy. Just because one can draw a square badly does not mean "triangle vs. quadrilateral" (BP6) should be labelled fuzzy; similar vagueness arises in all hand-drawn Bongard Problems. (For Bongard Problems in which fine subtleties of drawings, including small imperfections, are meant to be considered, use the keyword perfect.)


Sometimes the way a Bongard Problem would sort certain examples is an unsolved problem in mathematics. (See e.g. BP820.) There is a precise criterion that has been used to verify each sorted example fits where it fits (some kind of mathematical proof); however, where some examples fit is still unknown. Whether or not such a Bongard Problem should be labelled "precise" might be debated.

(Technical note: some properties are known to be undecidable, and sometimes the decidability itself is unknown. See https://en.wikipedia.org/wiki/Decision_problem .)

(See the keyword proofsrequired.)

One way to resolve this ambiguity is to define "precise" as meaning that once people decide where an example belongs for a reason, they will all agree about it.


Sometimes the class of all examples in a Bongard Problem is imprecise, but, despite that, the rule sorting those examples is precise. Say, for some potential new example, it is unclear whether it should be included in the Bongard Problem at all, but, if it were included, it would be clear where it should be sorted (or that it should be left unsorted). A Bongard Problem like this can still be tagged "precise".

(If all examples are clearly sorted except for some example for which it is unclear whether it belongs to the class of relevant examples, the situation becomes ambiguous.)

On the other hand, sometimes the class of all examples is very clear, with an obvious boundary. (Keyword preciseworld.)


There is a subtle distinction to draw between Bongard Problems that are precise to the people making them and Bongard Problems that are precise to the people solving them. A Bongard Problem (particularly a non-allsorted one) might be labeled "precise" on the OEBP because the description and the listed ambiguous examples explicitly forbid sorting certain border cases; however, someone looking at the Bongard Problem without access to the OEBP page containing the definition would not be aware of this. It may or may not be obvious that certain examples were intentionally left out of the Bongard Problem. A larger collection of examples may make it more clear that a particularly blatant potential border case was left out intentionally.

CROSSREFS

See BP876 for the version with pictures of Bongard Problems instead of links to pages on the OEBP.

See both and neither for specific ways an example can be classified as unsorted in an "precise" Bongard Problem.

Adjacent-numbered pages:
BP503 BP504 BP505 BP506 BP507  *  BP509 BP510 BP511 BP512 BP513

KEYWORD

fuzzy, meta (see left/right), links, keyword, right-self, sideless

WORLD

bp [smaller | same | bigger]

AUTHOR

Aaron David Fairbanks

BP876 Precise sorting of potential examples vs. not so.
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COMMENTS

Left Bongard Problems do not have to sort all relevant examples; if they would leave some border cases unsorted, it just has to be clear precisely which examples those would be.


Often a precise divide between values on a spectrum comes from intuitively "crossing a threshold." For example, there is an intuitive threshold between acute and obtuse angles. Two sides of a Bongard Problem on opposite ends of a threshold, coming close to it, are interpreted as having precise divide between sides, right up against that threshold.

CROSSREFS

See BP508 for the version with links to pages on the OEBP instead of images of Bongard Problems.

Adjacent-numbered pages:
BP871 BP872 BP873 BP874 BP875  *  BP877 BP878 BP879 BP880 BP881

KEYWORD

hard, notso, challenge, meta (see left/right), miniproblems, creativeexamples, assumesfamiliarity, structure, presentationinvariant

WORLD

bpimage_shapes [smaller | same | bigger]
zoom in left (bpimage_shapes_exact_sort)

AUTHOR

Aaron David Fairbanks

BP913 Bongard Problems in which fine subtleties of images may be considered with respect to the solution (no slightly wrong hand-drawings!) vs. other visual Bongard Problems.
BP1
BP160
BP199
BP210
BP211
BP213
BP216
BP217
BP223
BP312
BP321
BP324
BP325
BP335
BP341
BP344
BP348
BP367
BP368
BP386
BP523
BP529
BP530
BP531
BP532
BP533
BP551
BP557
BP559
BP564
BP816
BP852
BP859
BP860
BP861

. . .

BP5
BP6
BP72
BP91
BP136
BP148
?
BP119
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COMMENTS

Left examples have the keyword "perfect" on the OEBP.

Right examples have the keyword "ignoreimperfections".


Consider the difference in style between BP344 and BP24.


Hand-drawn figures in BPs are typically imperfect. A "circles vs. squares" BP may only show what are approximately circles and approximately squares. A pedant might append to the solutions of all Bongard Problems the caveat "...when figures are interpreted as the most obvious shapes they approximate."

This is the meaning of the label "ignoreimperfections". On the other hand, the label "perfect" means even the pedant would drop this caveat; either all the images are precise, or precision doesn't matter (see also keyword stable).


Even in BPs tagged "perfect", the tiny rough edges caused by image pixelation are not expected to matter. If the OEBP would indeed prefer users only upload pixel-perfect examples, a BP can be tagged with the stricter keyword pixelperfect.

E.g., for BPs having to do with smooth curves and lines, "perfect" only requires images offer the best possible approximation of those intended shapes given the resolution.


Most Bongard Problems involving small details at all would be tagged "perfect". However, this is not always so; sometimes the small details are intended to be noticed, but certain imperfections are still intended to be overlooked.


BP119 ("small correction results in circle vs. not") is an interesting example: imperfections matter with respect to the outline being closed, but imperfections do not matter with respect to circular-ness.


If a Bongard Problem on the OEBP is tagged "ignoreimperfections" -- i.e., it has imperfect hand drawings -- then other keywords are generally applied relative to the intended idea, a corrected version sans imperfect hand drawings. (For example, this is how the keywords precise and stable are applied. Alternative versions of these keywords, which factor in imperfect hand drawings, could be made instead, but that would be less useful.)




It may be better to change the definition of "perfect" so it only applies to Bongard Problems such that small changes can potentially switch an example's side / remove it from the Bongard Problem. That would cut down on the number of Bongard Problems to label "perfect". There isn't currently a single keyword for "small changes can potentially switch an example's side / remove it from the Bongard Problem", but this is basically captured by unstable or unstableworld. There is also deformunstable which uses a different notion of "small change". - Aaron David Fairbanks, Jun 16 2023

CROSSREFS

See BP508 for discussion of this topic in relation to Bongard Problems tagged precise.


Stable Bongard Problems are generally "perfect".

Pixelperfect implies "perfect".


The keywords proofsrequired and noproofs (BP1125) have a similar relationship: "noproofs" indicates a lenience for a certain kind of imperfection.

Adjacent-numbered pages:
BP908 BP909 BP910 BP911 BP912  *  BP914 BP915 BP916 BP917 BP918

EXAMPLE

Many Bongard Problems involving properties of curves (e.g. BP62) really are about those wiggly, imperfect curves; they qualify as "perfect" problems. On the other hand, Bongard Problems involving polygons, (e.g. BP5) often show only approximately-straight lines; they are not "perfect" problems.

KEYWORD

meta (see left/right), links, keyword, wellfounded

WORLD

visualbp [smaller | same | bigger]
zoom in left (perfect_bp)

AUTHOR

Aaron David Fairbanks

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