Concerning this boring nonsense:
https://book.simply-logical.space/src/text/2_part_ii/5.3.html#
Funny idea that anybody would be interested just now in
the year 2025 in things like teaching breadth first
search versus depth first search, or even be “mystified”
by such stuff. Its extremly trivial stuff:
Insert your favorite tree traversal pictures here.
Its even not artificial intelligence neither has anything
to do with mathematical logic, rather belongs to computer
science and discrete mathematics which you have in
1st year university
courses, making it moot to call it “simply logical”. It
reminds me of the idea of teaching how wax candles work
to dumb down students, when just light bulbs have been
invented. If this is the outcome
of the Prolog Education Group 2.0, then good night.
Hi,
Breaking News from the French conference of
philisophy professors in education. They launched
the Local AI Emacs Mode initiative to bring
new technology to even most remote corners
of the earth, such as the Poor South, i.e.
Spain, Brasil, Argentinia, etc..
It consists of:
- **org.joe:** This is a numpy library that
can solve large band matrices via storing
them on floppy disk. One speaker of the
philosophy conference said, this is ideal
to demonstrate algorithms such as Stable
Diffusion, it might take a month though
to generate an image but it servers its
educatinal goals for Low-Resource teaching.
- **org.sleepy:** This is a sympy library that
can also do natural deduction. It uses
very natural communication means such as
E-mail. Its especially useful together with
org.joe, since it will notify the user when
to change a floppy disk via E-mail.
- SWI-Prolog integration of Local AI:
org.joe has a R binding, which has SWI-Prolog
binding, which has a Janus Python binding, which
has a JSON web server binding, etc.. etc.. And
org.sleepy can be controlled via their brand new
XPCE, the Emacs that runs in a Mac/Windows Window.
But most Low-Resource teachers and students will
not be able to use it, since they have only
an ASCII terminal console on a 32-bit Unix.
Bye
Mild Shock schrieb:
Concerning this boring nonsense:
https://book.simply-logical.space/src/text/2_part_ii/5.3.html#
Funny idea that anybody would be interested just now in
the year 2025 in things like teaching breadth first
search versus depth first search, or even be “mystified”
by such stuff. Its extremly trivial stuff:
Insert your favorite tree traversal pictures here.
Its even not artificial intelligence neither has anything
to do with mathematical logic, rather belongs to computer
science and discrete mathematics which you have in
1st year university
courses, making it moot to call it “simply logical”. It
reminds me of the idea of teaching how wax candles work
to dumb down students, when just light bulbs have been
invented. If this is the outcome
of the Prolog Education Group 2.0, then good night.
Concerning this boring nonsense:
https://book.simply-logical.space/src/text/2_part_ii/5.3.html#
Funny idea that anybody would be interested just now in
the year 2025 in things like teaching breadth first
search versus depth first search, or even be “mystified”
by such stuff. Its extremly trivial stuff:
Insert your favorite tree traversal pictures here.
Its even not artificial intelligence neither has anything
to do with mathematical logic, rather belongs to computer
science and discrete mathematics which you have in
1st year university
courses, making it moot to call it “simply logical”. It
reminds me of the idea of teaching how wax candles work
to dumb down students, when just light bulbs have been
invented. If this is the outcome
of the Prolog Education Group 2.0, then good night.
Hi,
Here some test results when testing
Desktop and not the Web. With Desktop
Prolog versions I find:
/* SWI-Prolog 9.3.28 */
% 7,506,637 inferences, 0.578 CPU in 0.567 seconds
/* Dogelog Player 1.3.6 for Java (16.08.2025) */
% Zeit 803 ms, GC 0 ms, Lips 9367988, Uhr 17.08.2025 18:03
/* Scryer Prolog 0.9.4-592 */
% CPU time: 0.838s, 7_517_613 inferences
/* Trealla Prolog 2.82.12 */
% Time elapsed 2.315s, 11263917 Inferences, 4.866 MLips
Bye
Mild Shock schrieb:
Hi,
The paper by Shalin and Carlson from 1991
did not yet ring a bell. But it suggest testing
something with primes and freeze. Lets do
primes as suggested but without freeze. SWI-Prolog
seems not to the OG of GC. Putting aside Shalin
and Carlson, its an typical example of a lot of
intermediate results, that can be discarded by
a garbage collection. Every candidate number that
is not a prime number can be remove from the
trail they get unreachable in the first clause
of search/3. Besides this obvious unreachability
task, I don't have statistics or don't see immediately
where large variable instantiation chains are supposed
to be created. At least not in my Prolog system, since
a result variable is passed without binding it to a
local variable, this "shunting" happens independent
of neck tests and the "shunting" there. The result variable
passing is extremly simple to implement and could
be what is effective here besides the reachability thingy.
At least the 1 ms GC time in Dogelog Player show that
the reachability thingy is the minor effort or optimization
to get nice performance:
/* WebPL GC */
(1846.1ms)
/* Dogelog Player 1.3.6 for JavaScript (16.08.2025) */
% Zeit 2992 ms, GC 1 ms, Lips 2514202, Uhr 17.08.2025 17:44
/* SWI-Prolog WASM */
(4204.2ms)
/* Trealla Prolog WASM */
(23568.9ms)
The test code was:
test :-
len(L, 1000),
primes(L, _).
primes([], 1).
primes([J|L], J) :-
primes(L, I),
K is I+1,
search(L, K, J).
search(L, I, J) :-
mem(X, L),
I mod X =:= 0, !,
K is I+1,
search(L, K, J).
search(_, I, I).
mem(X, [X|_]).
mem(X, [_|Y]) :-
mem(X, Y).
len([], 0) :- !.
len([_|L], N) :-
N > 0,
M is N-1,
len(L, M).
Bye
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