Re: The skill of learning skills.



Lester Zick wrote:
On Mon, 02 Jan 2006 01:08:09 GMT, Risujin <risujin@xxxxxxxxxxx> in
comp.ai.philosophy wrote:
If we define intelligence as the skill of learning skills, we arrive at a gradual definition for intelligence. It is easy to see how a system may be capable of learning some kinds of skills but not others. The breadth/variety of learnable skills and their relevance to achieving the program's goal determines the degree of intelligence.

Now we need to define a skill, skill variety, and what exactly we mean by learning a skill. If we think of a skill as a state operator...:

* A skill is a procedure for inducing something to transition from one state to another. In other words, a set of instructions which the system is capable of following that predictably produces certain changes in the environment.

* A skill can be of any level of coarseness. We don't necessarily need to specify every action in detail. We can imagine abstract skills such as "drive a car" and reason with them without referring to sub-skills ("start the car").

* The definition of having learned a skill is trivial in this case--either the system can or cannot carry out the procedure. We don't necessarily need to constrain how the system carries out or acquires procedures.

* The power of a system can be measured in terms of the range of goals it is capable of achieving compared with the theoretical range of goals a system with the same inputs/outputs could possibly achieve.

* The intelligence of a system can be measured in terms of the range of skills it is capable of acquiring compared to the range of skills theoretically possible for it to perform. The intelligence of a system is its capacity for increasing its power over the environment.

Curiously, with this definition a static skill set would imply that the intelligence of a system decreases as its power increases. Only learning skills which expand the potential skill set of a system increase its intelligence.

An intelligent system would only require processing power to match human intelligence for time-constrained tasks. If we limit the domain of problems to non-timed goals, there is no reason at least a marginally intelligent system could not be built on a home PC today.

Maybe I should've made it more explicit but I wasn't actually going for a mechanical or any other kind of solution to the general intelligence problem. If you read carefully, the skills system I proposed falls far short of defining a mechanism. What I was suggesting is instead a possible measure of intelligence as an alternative to "we'll know it when we see it".

Okay. But how is your possible measure of intelligence superior to "we'll know it when we see it"? All the different schools of thought seem to have their own measure of what they're looking for in smarts.

The "we'll know it when we see it" definition is as bad as it gets. You cannot derive anything from such a definition except a yes/no answer with no reasoning.


My proposed measure is not unique. It may not be the best around either, I'm not claiming it is. It does have some predictive power though. I noted some interesting consequences after the definition. It is also more concrete than many other definitions. I was hoping we could tighten it up further, or come up with something else that is concrete.

A mechanism for producing/conforming to the behavior I describe above is the ultimate goal here but I'm not claiming to have anything remotely close to it now.

But there are plenty of people who do make exactly that claim. You seem to disagree with them. So how does your suggestion contradict what they claim?

Doubtless there are system which conform to the skills measure. It defines and measures intelligence. If there are intelligent systems they will rank somehow in this measure.


I don't see why we are looking for contradiction here.

-- Risujin
.



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