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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
BP365
BP393
BP505
BP508
BP509
BP511
BP524
BP571
BP812
BP813
BP847
BP865
BP894
BP895
BP939
BP1002
BP1111
BP1158
BP1271
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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

BP511 Noisy Bongard Problems vs. minimalist Bongard Problems.
BP10
BP25
BP37
BP40
BP42
BP48
BP58
BP60
BP64
BP65
BP66
BP73
BP82
BP98
BP105
BP106
BP109
BP116
BP123
BP127
BP128
BP130
BP131
BP132
BP135
BP136
BP162
BP165
BP174
BP181
BP183
BP192
BP194
BP201
BP202

. . .

BP859
BP962
BP1104
BP1122
BP1156
BP1219
BP1255
BP1271
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COMMENTS

Left-sorted BPs have the keyword "noisy" on the OEBP. Right-sorted examples have the keyword "minimal."


Noisy Bongard Problems include extra details varying between examples that distract from the solution property; more specifically noise is properties independent of the solution property that vary between examples. Minimalist Bongard Problems only vary details absolutely necessary to communicate the solution.


"Noisy" is different than the kind of distraction mentioned at distractingworld, which means the class of examples is distractingly specific, irrelevant to the solution, rather than that there are extra distracting properties changing between examples.


Bongard Problems have varying degrees of noisiness. Only include here BPs that are very noisy or very minimal.

CROSSREFS

See BP827 for the version with pictures of Bongard Problems (miniproblems) instead of links to pages on the OEBP.

See BP845 for noise in sequences of quantity increase.

Adjacent-numbered pages:
BP506 BP507 BP508 BP509 BP510  *  BP512 BP513 BP514 BP515 BP516

KEYWORD

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

WORLD

bp [smaller | same | bigger]

AUTHOR

Harry E. Foundalis, Aaron David Fairbanks

BP864 Bongard Problems in which all examples are easy to sort after knowing the solution vs. Bongard Problems in which examples can be hard to sort even after knowing the solution.
BP323
BP335
BP344
BP532
BP853
BP860
BP863
BP1005
BP1006
BP1119
BP1123
BP1132
BP1136
BP1137
BP1245
BP1271
BP1279
BP1280
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COMMENTS

Right examples have the keyword "hardsort" on the OEBP.


Contrast "hardsort" to infodense, where examples have a high amount of information, but perhaps after parsing all the information in the examples it is easy to sort them.


BPs labelled "hardsort" are likely to be labelled hard, but perhaps not--e.g. in BP323 the answer is easy to guess, but laborious to verify.

CROSSREFS

Adjacent-numbered pages:
BP859 BP860 BP861 BP862 BP863  *  BP865 BP866 BP867 BP868 BP869

KEYWORD

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

WORLD

bp [smaller | same | bigger]

AUTHOR

Aaron David Fairbanks

BP963 Bongard Problems in which small changes to examples can switch their sorting vs. Bongard Problems in which examples changed slightly enough remain sorted the same way.
BP1
BP4
BP15
BP72
BP211
BP324
BP325
BP335
BP344
BP348
BP367
BP368
BP523
BP816
BP860
BP861
BP920
BP935
BP937
BP2
BP9
BP11
BP14
BP34
BP62
BP1271
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COMMENTS

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

Right examples have the keyword "stable" on the OEBP.


For the purposes of this Bongard Problem, "small change" means adding to or removing from an arbitrarily small portion of the image. Other kinds of small change could be explored, such as making changes in multiple small places, translating, rotating, scaling, or deforming the whole image slightly (see also keywords deformunstable vs. deformstable), or even context-dependent small changes (e.g., changing the shadings slightly in BP196, or making small 3d changes to the represented 3d objects in BP333), but they are not considered here.


In a "stable" Bongard Problem, no small change should outright flip an example's sorting. It is allowed for a small change to make an example sorted slightly more ambiguously.


Small changes that make an example no longer even fit in with the format of a Bongard Problem are not considered. (Otherwise, far fewer Bongard Problems would be called "stable".)


For whether small changes make an example no longer fit in with the Bongard Problem, see unstableworld vs. stableworld.


If a Bongard Problem is shown with imperfect hand drawings (keyword ignoreimperfections), it is fine to apply the keyword "unstable" ignoring this. For instance, a hand-drawn version of BP344 would still be tagged "unstable", even though it would show examples wrong by small amounts.

(Note: a BP would only be tagged "ignoreimperfections" in the first place if the underlying idea were such that several small changes could make an example switch sides, no longer fit in with the format of the Bongard Problem, or otherwise be ambiguously sorted.)

CROSSREFS

Stable Bongard Problems are generally perfect and pixelperfect.

Gap (technically) implies stable. (However, in practice it has seemed unnatural to tag BPs "stable" when ALL small changes render certain examples unsortable, as is sometimes the case in "gap" BPs.)


Unstable Bongard Problems are often precise.

Stable Bongard Problems tend to either be fuzzy or otherwise either have a gap or be not allsorted.


See BP1144, which is about all small changes making all examples unsortable rather than some small change making some example switch sides.


See BP1140, which is about any (perhaps large) additions of detail instead of small changes.

Adjacent-numbered pages:
BP958 BP959 BP960 BP961 BP962  *  BP964 BP965 BP966 BP967 BP968

EXAMPLE

BP1 is unstable because it's possible to change nothing slightly by adding a pixel to end up with something.

KEYWORD

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

AUTHOR

Aaron David Fairbanks

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