artificial smartness

im bored. im going to try and make an AI written in python with the potential for infinite scalability. im going to start it on my desktop then move it to a debian cluster when it gets to large. woudl you like to help me? first things first, i should work out the flowchart for the decision making engine. wikipedia has a good looking definition baout the decision making process, i think ill start there. would /prog/ like to help me figure out how to implement these? the first problem i want to give my pet is climbing over a brick wall.

Outline your goal and outcome.
Gather data.
Develop alternatives (i.e., brainstorming)
List pros and cons of each alternative.
Make the decision.
Immediately take action to implement it.
Learn from and reflect on the decision.

i should work out the flowchart for the decision making engine
A potential apprentice of the Mentifex craft.

let us be the ones to create the technological singularity without the constraints of FAI

make the body a girl so we can have non bitchy women at last

Port Mentifex's AI Mind to Python.

http://granite.sru.edu/~conlon/python/eliza.py

The German artificial intelligence for Linux http://cyborg.blogspot.com/2009/11/linux.html 64-bit supercomputers is currently the most advanced Mentifex AI Mind, but it warrants porting into a JavaScript tutorial version for memetic purposes of AI diaspora and for incentivising ports into further languages (both programming and natural languages).

Therefore yesterday I was translating the http://code.google.com/p/mindforth/wiki/InFerence module for machine reasoning from Forth into
http://cyborg.blogspot.com/2009/08/javascript.html JavaScript and I ran into problems with how to translate the following Forth neural-net AI code:

1 t +!  \ increment t to store direct object; 30jan2013
seqtqv @  7 psi{ @  t @  0 psi{ !  \ dir. obj 30jan2013
 40  t @  1 psi{ !  \ activation of direct object 30jan2013
seqtqv @  7 psi{ @  t @  8 psi{ !  \ enx 18dec2012; 30jan2013
dobseq @   t @  0 de{ !   \ so noun can be found; 30jan2013

The code above in Forth and below in JavaScript stores the direct object "child" in the inference formed when we tell the AI that "Eve is a woman." Since the AI knows that "Women have a child", the artificial Mind infers the possibility, "Eve has a child." Forth fetches the concept of "child" from one point in the mindgrid array and inserts the stack-riding value into another point. To code the same neural-net algorithm in JavaScript, it was necessary to create the special variables "seqdob" for the sequential direct object and
"seqenx" for the sequential English transfer. Notice how verbose the code is in JavaScript:

t = (t+1);  // increment time to store direct object; 18mar2013
Psi[seqtqv].psiExam(); // obtain seqdob from Psi array; 18mar2013
seqdob = psi7;  // to serve as "psi0" in next insertion 18mar2013
seqenx = psi8;  // to serve as "psi8" in next insertion 18mar2013
Psi[t].psiExam(); // expose values for change of some; 18mar2013
Psi[t] = new psiNode(seqdob,40,psi2,psi3,psi4,psi5,psi6,psi7,seqenx);
enLexicon[t].enExam();  // expose values even if empty; 18mar2013
enLexicon[t] = new enNode(dobseq,en1,en2,en3,en4,en5,en6,en7,en8);

http://www.scn.org/~mentifex/AiMind.html is now "Artificial General Intelligence with machine reasoning by inference", but the mind-modules http://code.google.com/p/mindforth/wiki/AskUser
http://code.google.com/p/mindforth/wiki/KbRetro

have yet to be ported from Forth into JavaScript. The current AiMind.html creates only a silent inference visible as array-elements in Diagnostic Display Mode when the AI is run in MS Explorer.

If these Mentifex AI Minds and other projects catch on with some burgeoning pre-Cambrian-esque explosiveness, behold soon an emergent job market for AI coders and AI installation technicians.

he probably has some kind of schizophrenia
http://en.wikipedia.org/wiki/Schizophrenia

at least i hope he don't write all those dated comments by hand