[LOCKSUIT]

Put another way, my old plan may have learned cues and action programs, but, it has to think deep about what the goal is, and related knowledge ex. about how a type writer functions and looks like and all its parts ex. metal spokes are flat on top etc, and metal is hard and not soft.

It has to come up with the plan of actions, yes, but, then it has to use what it has learned, and leverage it so it can anologate it to different situations/reflections and come up with a plan fast instead of making one from complete scratch with huge search space.

[LOCKSUIT]

You may wonder though, ok, so this baby is a bad idea, but, if there's no baby/human, then who caries plans out for real? So someone has to learn motor actions, sequences, by Reinforced Learning, and link them to visual or text knowledge like 'throw arm' or 'run a bit to the left' or 'put the block on top and shoot it 3 times'. And so then we have a bunch of little pieces of motors, that can be built into hierarchical long sequences, just like building blocks.

After AGI acquires bodies, it will then also do external discovery, using feedback. Tests.

[LOCKSUIT]

Imitation is where we accelerate at learning motor programs, not just knowledge taught.

[LOCKSUIT]

Having been taught 2 hierarchies, one of motor and one of text knowledge (sequence sensory (words are like non-sequence sensory)), and 'linked', you now narrowdown its search space, using old knowledge, SP, convincing, you know (as explained well in the last posts).

[LOCKSUIT]

You might be able to evolve the AGI program using allowed modifications to nodes and links. Or you could code the whole thing if you're smart enough.

AGI uses knowledge and generalization to discover desired answers, yes, inference. Certainty some evolutionary algorithm can be added to AGI to speed it up, but, the reason it doesn't have a huge search space in the first place isn't because of the evolutionary algorithm, so, it may not even be needed!

[LOCKSUIT]

How often, do you ivan or korrelan, as a human brain, generate 100 possible answers like a evolutionary algorithm? I never generate that many ideas. I always just 'have the answer' on my tongue.

Not 100% sure though, but definitely to some extent! Never 10,000. I don't even have time to generate that many !!!!!!!!!!

[LOCKSUIT]

So ya, we pass down to our children the imitated knowledge and motor actions (senses are actions too, just, motor must be MOTOR!, to actually carry things out).

We're giving all the learned important building blocks (knowledge), and how to do some of them.

Then man has desires, ! We then work in our gifted world of teachings, and utilize them of course.

[Korrelan]

How often, do you ivan or korrelan, as a human brain, generate 100 possible answers like a evolutionary algorithm?

This depends on how you imagine the brain to function.

In my opinion an idea is constructed from 100’s of sub-conscious snippets of knowledge.

Evolutionary algorithms are not the total answer, but a similar schema does play a part in our intelligence.  When we are trying to figure out a problem space, we tend to hold the main facets of the problem in ‘short term memory’ and then mentally apply different parameters whilst mentally considering the repercussions/ outcomes.

This smacks of a genetic algorithm schema, where proven past experience (wisdom) is mentally applied to a set of parameters.

Let’s take a simple example… is it quicker to walk or run?

Your sub conscious is doing 90% of the work here, you are mentally conceptualising the parameters of walk/ run, you didn’t need to think about the concepts individually… you just knew automatically what walk/ run meant along with their relevant parameters, speed, etc. 

All your consciousness has to do is consider the question being asked and compare the relevant speed parameters… and then speak/ write the answer.

So in a way I believe we do have 100’s of sub-ideas for every thought/ idea we have.

 

[LOCKSUIT]

"When we are trying to figure out a problem space, we tend to hold the main facets of the problem in ‘short term memory’ and then mentally apply different parameters whilst mentally considering the repercussions/ outcomes."

What we hold in Working Memory is the question/s. We do bring into WM related things / things that come with it, and consequences/appeals vote in on the decision/s found based on old knowledge.


"This smacks of a genetic algorithm schema, where proven past experience (wisdom) is mentally applied to a set of parameters."

We use Long Term Memory to help discover the answer/s. Helping knowledge need not be proven valuable/ranking at all.


" "is it quicker to walk or run?" "

You imitate back the answer "it is quicker to run". You just need a little, support/validation comparison. Here we already have the answers, we just need to narrowdown. We may know 'it is faster to jog'. Or we may see 'is it [quicker] to walk or run?' and so 'run' wins. (litterally lol woho)