The last couple of days I’ve been pondering how in a hell you can squish all capability that is required into CC so that you can do high order functions w/o resorting to additional neuron circuitry.
TM is normally thought of a sequence memory and thats it !! That is how it was tested I think… taxicab, temperature datasets come to mind … but if that is all about it is pretty dumb memory and we have to implement alot of additional logic to make workable system…
Simply adding structure to the items solves the problem. How ? What ?
In ML language we need to memorize State and Action pairs.
In TBT language we need to build sequence of at least : Location, Feature and Motor Command.
The L4<=>L6 loop thus passes to the TM not only the Location but also the Cmd it used.
So we still store variable order sequences but that sequence has a structures that allows you to :
- Planning & RL
- making decision …afaik L4 pass down Cmds that is then filtered by BG!
- The dynamic MODEL thus is in RefFrame with a metric based on the Grid storing the whole interaction as State:Action sequence
Prove me wrong ?
also if we accept what ML thought us it has to be : Cmd1, Loc1:Cmd2 , Loc2:Cmd3,…
instead of : Loc1:Cmd1 , Loc2:Cmd2,…