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AIRmichael

Neuron generator

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Hey, I made something new, a neuron generator. Neurons have 1/n inputs and 1 output. Allthough this is only for 1 purpose ( all the same neurons).The same system can be used for several other outputs. This is what it does: the user tells a number. ( like 100 ). The neuron keeps modifying its adjustment. ( eventually it "knows" how to go to 100). This is what 1 neuron normally does. Now every time the neuron is calculating its output, another neuron is added. The output is the neuron with the best score. After the best output is displayed, ALL neurons are getting the adjustment of that best neuron. With 1 neuron, it takes about half a minute/a few min, with 1 point adjustment over 14% randomness. With the neuron generator, it takes only 10/30 seconds. It keeps adding neurons. ( The limit atm is 10.000.000 neurons ). [edited by - AIRmichael on July 26, 2002 3:04:44 PM]

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thats pretty confusing, what are you sayin you have coded learning "" neurons or something ? please elaborate .

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The number of neurons increases, and the modifications of the best neuron is used again. I just found out, rand()%50 as coincidence, and only 1 signal strenth, it STILL finds the number! After about 300 neurons , 300+299+298... n neuron calculations.

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Ummm... could you explain just a little more explicitly? You''re kinda losing me on what you mean by modifications, signal strength, and where rand () % 50 came in. Also, how many inputs do the neurons have? What are these inputs?

Maybe a code sample would show this better.

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The output relies on 2 things, randomness + the adjustment of the neuron. When a neuron gets closer guessing to the user defined number, lets say 100, it gets a score. If that score is better, then the neuron checks what it did before. +adjustment is less this time , for example. So it makes the adjustment less. (adjust the output).

With "modify" i mean, adjusting the adjustment of all the other neurons, to the settings of the best neuron.

The coincidence, is random, so its the moment when the output relied on randomness, and isnt better because of its new adjustment. With 1 neuron, and with a to big coincidence, it won''t never learn better, cause it thinks it "improved" itself, but it was just randomness. So it leads it to the wrong track. It went worse for example, but the neuron thinks its his fault, and does something else to fix it. Due the fact that it relies to much on coincidence, it wont get any better. With new neurons added in realtime, it gets smarter and smarter. And finds the number eventually.

Eventually, a new neuron is added.
Wow just found out, that with 500 coincidence, and 1 effectiveness, it still finds the number, after 300 neurons. So its pretty clear that it can find all numbers, no matter how much coincidence sounds, but it has to have enough neurons.

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it seems you are generating your score based on a known number, how will you evolve it without a "given" to score by?


Dreddnafious Maelstrom

"If i saw farther, it was because I stood on the shoulders of giants."

Sir Isaac Newton

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You always have to give a neuron a score, else it wont envolve. BTW that number can be changed to something else though, it doesnt matter. But it has to know when its improving or not. Allthough with randomness in it included as well.
( yeah its like the dice).

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