Croesus, addressing Cyrus, says —
τὰ δὲ μοι παθήματα ἐόντα ἀχάριτα μαθήματα γέγονε.
My sufferings, though painful, have been my lessons.
— Herodotus • 1.207
Croesus, addressing Cyrus, says —
τὰ δὲ μοι παθήματα ἐόντα ἀχάριτα μαθήματα γέγονε.
My sufferings, though painful, have been my lessons.
— Herodotus • 1.207
What answers to the Meno Paradox
Comes in the moment of realizing —
Gathering together the building blocks
Is just the beginning of the building.
Re: R.J. Lipton and K.W. Regan • Who Invented Boolean Functions?
One of the things it helps to understand about 19th Century mathematicians, and those who built the bridge to the 20th, is that they were capable of high abstraction — in Peirce’s case a cut above what is common today — and yet they remained close enough to the point where abstract forms are teased away from the concrete materials of mathematical inquiry to maintain a sense of connection between the two. There are few better places to see this connection than in the medium of venn diagrams. But venn diagrams are such familiar pictures that it’s easy to overlook their subtleties, so it may be useful to spend some time developing the finer points of what they picture.
There are actually several types of boolean functions depicted in the typical venn diagram. Each has the boolean domain or one of its powers
as its functional codomain but its functional domain need not be limited to a finite cardinality. To sort their variety, consider the array of functional arrows in the following figure.
Suppose is a universe of discourse represented by the rectangular area of a Venn diagram. Note that the set
itself may have any cardinality. The most general type of Boolean function is a map
This is known as a Boolean-valued function since only its functional values need be in
A function of the type is called a characteristic function in set theory or an indicator function in probability and statistics since it can be taken to characterize or indicate a particular subset
of
namely, the fiber or inverse image of the value
for which we have the notation and definition
The notation is often used for the characteristic function of a subset
of
Putting all the pieces together then, we have
To be continued …
Re: Peter Cameron • Addition and Multiplication of Natural Numbers
The interaction between addition and multiplication in the natural numbers has long been an interest of mine, leading to broader questions about the relationship between algebra and combinatorics. My gropings with those enigmas led me to the structures of Riffs and Rotes, extracting what we might think of as the “purely combinatorial” properties of primes factorizations. Thinking of the additive structure of the positive integers as embodied in their total linear ordering, the following two questions arise.
cc: Category Theory • Cybernetics • Ontolog Forum • Peirce List (1) (2) • SeqFan
cc: FB | Riffs and Rotes • Laws of Form • Structural Modeling • Systems Science
Computing, in its way, and science, in its broader way, both involve the relation between what appears limited and what appears not. Whether you believe in divinity or not, and whether you believe that humanity contains a spark of divinity or not, we have to acknowledge that our powers as oracles are limited and, even if they were not, problems of relative computability would still arise in the striving of oracles to communicate with one another.
How many times do I repeat the same experience? Before I come to see it as the same experience?
A trendy misunderstanding has reared its head as to what the discipline of computing, indeed the logic of science, are all about. I blame Penrose, of course, but he is only the most recent promulgator of the recurring misunderstanding.
There are only a countable number of computable functions, so it’s no surprise a natural system picked at random will have non-computable functional features. Saying not all natural systems are computable is like saying not all poems are sonnets. Writing a program to model a significant aspect of a natural system is like writing a sonnet to express a significant aspect of human experience. It’s a voluntary limitation programmers and poets accept for the sake of their elective-effective art.
And both have their uses.
Re: R.J. Lipton and K.W. Regan • Who Invented Boolean Functions?
The question recalls recent discussions of discovery and invention in the mathematical field, bringing back to mind questions I’ve wondered about for as long as I can remember.
Speaking as an unreconstructed Platonic realist, I am tempted to say Boolean functions are mathematical objects which cannot be invented, only discovered. But speaking as a semiotic constructivist I would have to concede we do indeed invent all sorts of syntactic systems for talking and thinking about these mathematical objects. And some calculi can even be better than others for the purpose of calculation, a fact repaying us to consider the alternatives as they work out in practice.
On the third hand, I have more lately been thinking the concepts of discovery and invention, being human constructs like the proverbial concepts of particles and waves, may not be adequate in the final analysis to articulate the reality of the process at hand. It may well be all these questions are more like the question —
NB. This page is a work in progress. I will have to dig up some still older notes from the days of pen and paper before I can remember how I left things last.
Here are some notes on a computational approach to category theory I started working on back in the 1980s, all of which work as yet remains in the “Schubert Category” of unfinished symphonies.
It helps me a little bit to write the names of categories in the plural, so as not to confuse them with individuals. It also helps if I treat the arrows of Arr(C) as the primary entities in the category C, recovering the objects of Obj(C) as secondary entities by collecting all the entities that appear in s(f) = Source(f) and t(f) = Target(f) as one ranges over all of the arrows f in Arr(C).
The last time that I tried to do “categories by computer”, I was using data structures that had the following shapes:
Category C o
/|\
/ | \
... | ...
|
Arrow f o
/ \
s t
/ \
s(f) o o t(f)
A functor, then, is something I picture like this:
Functor F o
. | .
. | .
. | .
. | .
Category C o o o Category D = CF
| ./ \. |
| . / \ . |
| . / \ . |
| . / \ . |
Arrow f o o o o Arrow fF
/ \ . . . . / \
/ .\ . . /. \
s . t . . s . t
/. \ . . / .\
o o o o
x y xF yF
This is a rough sketch of the actual data structures that I used to represent a functor F as a “matching” between the parallel items of categories C and D.
NB. I have reverted to the convention I was accustomed to use at the time, where all operators are applied on the right of their arguments.
What the picture says is that the functor F : C → CF takes each arrow f in C to an arrow fF in CF, and each object x in C to an object xF in CF, in such a manner that (fs)F = (fF)s and (ft)F = (fF)t. To be a functor, F must satisfy the following two systems of equations:
(f ∘ g)F = fF ∘ gF, for all composable f, g in Arr(C).
That was just how I kept track of things on the computer.
It is, of course, more usual to draw a functor square in the following manner, where we get one such picture for each object x and arrow f in C.
F
x o-------->o xF
| |
| |
f | | fF
| |
v v
y o-------->o yF
F
Re: Next Polymath Project • What, When, Where?
Here’s a bit of data on the Theme One Program I worked on all through the 1980s. My aim was to develop fundamental algorithms and data structures to support an integrated learning and reasoning interface. I wrote up a pilot version of the program well enough to get a Master’s degree out of it but still haven’t gotten around to writing up the complete documentation. Below is a link to what I’ve put on the web so far.
I see this project as being related to Tim Gowers’ Proposal on the Mathematics of the Origin of Life, since one of the reasons for doing this work was to get information about the threshold of systems-theoretic complexity necessary to support a capacity for inquiry.
By the end of the 80s, and especially as I returned to grad school in systems engineering during the 90s, my work on this program gradually morphed into a broader study of what I began calling “Inquiry Driven Systems”. The conceptual background for this study is outlined in the following proposal.
More discussion to follow as I get time …