Segmenting the Intelligent from the Non-Intelligent
It seems we should first do binary classification:
Is this system intelligent? YES / NO
Then we can do [gradient based segmentation] within intelligence:
Where does this intelligent system lie on an evaluation scale? [Gf...Gc...Gf]
So we lead to the questions:
- What are the innumerable variables that could be measured for any intelligent system?
- Is there a coefficient that scores each variable as additive toward a global variable or are variable coefficients always environmentally bounded?
- How do you compare two systems if they have different contextual environmental boundaries?
Maybe lets put this in plain terms:
Assuming you have a system that is deemed “intelligent,” what do you measure in order to determine that the measures are correlated with the system being able to act towards an outcome (either local or global), and further how would you compare these systems if they reside in different environments? This is the topic of Jose Hernandez-Orallo's book: The Measure of All Minds
The last portion would require a global action vector, or a generalized action vector for intelligent systems. Discovering if there is in fact a generalized action vector (AKA answering the question “What is life about”) would be a significant achievement.
Is intentionality of action a determinant of intelligence: If a system didn't want to do anything how would a system that did, rate in comparison?
Is the idea of a ratings system even coherent? Why would we want to rate or compare systems? We only do that to allocate resources to be efficient to some ends – back to the intention based evaluation.
Everything in intelligence evaluation seems to need an action vector:
Intention > Action > Result
Why should we make the distinction between intelligent and non-intelligent systems? What purpose does it serve to segment these two things?