From: Petter Wingren-Rasmussen (petterwr@gmail.com)
Date: Fri Feb 20 2009 - 07:39:28 MST
As I mentioned in *this <http://www.sl4.org/archive/0902/19805.html>* thread
i think an AGI with hardcoded dogmatic rules will have some serious
drawbacks in the long run. I will try to show an alternative here, that
still will remain
friendly to humans.
I base this on previous work with AIs in gaming theory such as the tit for
tat tournaments <http://en.wikipedia.org/wiki/Tit_for_tat>
Note that the ideas below are rough outlines and that my programming skills
are rudimentary.
(Cognivitive-behavioural theory is my field.) My reason for posting this is
that you hopefully will point out problems/faults that I havent noticed
myself, and maybe even refer me to similar work that's already been done.
Now lets start with a lot of simple Ais (semirandom neural networks) in a 2
dimensional virtual landscape, arranged like a checkerboard (but a lot more
squares) where each ai take up one randomly assigned slot and can move one
step at a time in any of the eight directions (like the king in chess).
The Ais are able to move around freely and detect if they get close to
another AI. Each AI also has zero points from the start.
Input channels: direction and distance to nearby Ais, detecting output from
adjacent Ais, change of current points. They will also be able to recognize
and remember each individual AI.
Output channels: movement command, some kind of output, binary string will
be sufficient.
Rough outline of points:
Using a certain amount of cpu will cost 1 point. (To avoid slowing down the
whole system unnecessarily with meaningless loops.)
Creating output will cost 10 points.
Detecting output from adjacent Ais: will give a lot of points 1st time its
detected from every individual AI, but will decrease rapidly if detected
from the same AI several times.
Say 1000 points for the first time, 100 second,10 3rd and 0 for the fourth
time. The points received will increase by 1 point per turn that no input is
received from that particular AI.
Let's take the 10% that reach 100 000 points first and make 10 new versions
of each with slight variations(through some kind of genetic algorithm). Then
repeat the experiment for a few generations.
A behaviour similar to the winners of the tit for tat tournaments can be
expected to develop.
It is important that similar rewardsystems are kept throughout the
development (ie you earn a lot from recieving and only loose a little from
giving).
After a while the Ais can be expanded to be more complex and criterias for
points can be tougher both socially (partial imitation (which is the
simplest form of empathy behaviouristically speaking),
linguistically(greeting phrases, farewell phrases, eventually learning
speech) and spatially (ability to navigate around obstacles and through
labyrinths, adding more dimensions, manipulating objects etc.)
When the tasks differs in this way, one thing will remain constant - the AIs
that keep on doing what they do when they get points will prosper and a
mechanism for encouragement/happiness has been implemented.
Eventually it might be possible to introduce them into a virtual world like
second life and evolve more complex rating systems (ie ratings by human
avatars, moneys earned, objecs created). After that, anything would be
possible.
The whole point of this venture is that I believe it will result in a
social AI that intuitively reacts and thinks in the same way that we do.
Im looking forward to your criticism.
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