Seeing red

[emjay]

Okay, I'm game to talk about it if you want to start your thread but not right now cos I'm just about to go to bed. What triggered this line of thinking?... did you want to use a neural network for the game mechanics?

I want to see how many variables need to interact to make the results completely unpredictable by the player or programmer.

Sorry about the slow reply I'm a bit distracted now because all our talk about the book has got me excited about it all over again and I want to go through it again, this time using Emergent. So I think I'm now going to bow out of this thread, but you guys are welcome to keep it going and I'll still read it from time to time. It's given me a lot of insight and I feel like I'm in a new phase of understanding with plenty enough to keep me going so it's served it's purpose for me

I think it would be pretty cool if you could do that cos it looks to me like it could have uses as a random number generator I'm afraid I don't know what to say except good luck with your project... I'm sure it makes sense to you You did get me thinking though about trying to model an 'evolving' shape in a neural network. Say you have a cube with nine 'panels' on each face, like a Rubik's cube, and each of those panels represents a pressure sensor and has a corresponding neuron in the input layer, then it would be interesting to see what representations and expectations form in the network given simulations of what could happen to it... such as just laying on a table (ie nine panels active)... being pushed off a table (nine panels + one on an adjoining face... representing pushing it along with a finger... then some of the nine opposite from where the pressure is turning off as the cube hangs over the edge before falling... then the random way it bounces, rolls, and comes to rest at the bottom, meaning 3 panels each from two adjoining faces if it bounces on an edge, and 1 each from three faces if it bounces on a corner etc... no pattern in the which faces/edges/corners hit first after the fall but you would still expect a general pattern of it's movement to emerge... the rolling motion. Then to 'evolve' this thing you would just add panels/mini-cubes to the surface and add corresponding neurons to the input layer. I'm just curious to see what sort of representations would form and if it could come to represent its own shape. I'm just thinking that about the question of what could be the simplest hypothetical organism to model where you could see, scaled down massively, the principles at work in the human brain.