I was thinking about Neurel networks and memory an human brain. And about how humans can remeber stuff. You can easily remember stuff in your short-term memory. But remembering sruff that is not in it, requires a stimulus. In my perception (I don't know whether it is right or wrong), you can do so cuz you can make a loop on all the stuff in your short-term memory cuz it is small enough. But your long-term memory have incridible amount of data, as proven a human never forgets anything, you remember every smell every event every picture, even if you saw it for less than a second, you just don't know that. So it is impossible to traverse it unless the part you are traversing are well structured (from understanding), or from a stimulus from the short memory. To see that, see what you do when you try to remember something, you always try to remember something you aculally remember then see if that recalls something, if not, you remember the second thing and so on, till you find what you want to remember or you fail.
I am still thinking, what that have to do with a neural netword representation ? I don't think it is simple as simple recursive neural networks. As in NERO game (http://nn.cs.utexas.edu/NERO/about.html) skills are encoded in the neural netword structure. What is the difference between skills and knowledge in the storage context ?
Another thing, neural networks and genetic algorithms have united in that game (and long time before it too, that game's just testing modifying the net structure not just the weights), but I think there must be a way to involve SWARM in a more sophisticated way to enhance learning. I am also thinking about some informed neuroevolving agorithm, not only making offsprings by random mutations and combinations, but by have an insight about the neural network way of working, although humans don't know it yet; a neural network, in my perception, is just a big generic boolean formula.
This is all ideas of research, which I hope it wasn't made before.