Yes, there are a number of models to qualify as being “intelligent” (or not) where for a robotics beginner it’s David Heiserman, for someone who wants to input game show poetry and all that it’s a Watson, and for in-between very neuroscientific methods is HTM and associated Thousand Brains theory.
After accounting for Arnold Trehub’s simplified diagram for the human brain I get this comparison:
Above illustration is from: https://sites.google.com/site/intelligencedesignlab/home/ScientificMethod.pdf
What makes a Heiserman simple circuit/interaction able to produce complex behavior is what happens (temporally) over time, while racing from one timestep/thought to the next, in a direction that depends on what it was thinking about minutes or seconds ago. Action outputs become pulse/spike train signals for fine control of muscle forces. When everything is going well it’s switching high confidence motor signals back and forth to maintain balance at a given (circular or linear) navigational angle. One tiny thing that it has not yet experienced can cause a total change in what it is doing before going back to earlier task, or not, depending on whether it (normally used) starts off a new memory location with current motor actions for data, or guesses entirely new actions.
The model to demonstrate navigational behavior has to ahead of time predict motor actions needed to stay out of the way of an approaching shock zone that sends confidence in usual actions to an all time low, which causes reguessing that leads to avoidance of food while getting zapped. The virtual critter then gains the common sense to go around the zone then wait for the food to be in the clear. There are then dilemmas where wanting to do both conflicting things at some time causes amusing impatience, as in living animals. It will never win a genius level game show but this is an excellent test for navigational level intelligence. At the “intellectual” level are vocal motor actions and associated networks for “drawing a picture” of something we can in our mind navigate, predict from. We need both to talk and walk at the same time, not single thing controlling both.
More information is at:
Numenta has an interesting model that was easy to this way qualify as intelligent, which drew me to this forum. Adding “prediction” raised the bar another notch but it’s more like something that a properly functioning system I’m familiar with all together produces, not new thing that has to be added to an existing circuit diagram or algorithm. I want what I have for a definition to withing its given limits work with what others have, make sense to areas of cognitive science it applies to. It’s something I put a lot of thought into, I needed to share with you in this thread.