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And where is the source code? So far from this other article you've linked to I can only see formulas and theory. There is a vague explanation as to what the robots are accomplishing and still I do not see the literal code driving these bots to "evolution". Lmao.
It is impossible to generate a random program because random numbers are not literally possible. It is all weighted and still I haven't seen a programmer's argument to come back and prove these experiments as being exactly like biotic life.
You are accepting this article the same way faith strong people accept the fact that there is a creator. (this line is meant to be rhetorical).
And you don't understand why random numbers are important - they are the base for how this program is supposed to develop.
These six sensory inputs were scaled to a range of [−1; 1]. In addition to the sensory inputs the neural network also comprised a bias input set to a constant value of −1, which was used to encode the neuron firing threshold. These seven inputs were connected to three neurons in a hidden layer, which in turn connected to three output neurons. The strength of these 33 connections was determined by 33 genes, whose values ranged from 0 to 255 (i.e., 8 bit resolution per gene). The activation of each of the six hidden and three output neurons was calculated by multiplying each of its input values by its associated connection weight, summing over all inputs, and passing the sum through the continuous tanh(x) function to obtain the neuron's activation value in the range of [−1; 1]. The activation value of the first output neuron controlled the left motor speed, the second the right motor speed, and the third whether or not the successfully pushed food items were shared with other group members.
The foraging efficiency of each group was evaluated 10 times for 60 seconds and the inclusive fitness of each individual was estimated according to the number of food items collected and not shared + the number of food items that other group members collected and shared (these values being multiplied by c and b/7, respectively). The probability of the genome of a given robot to contribute to the next generation was directly proportional to the robot's inclusive fitness (roulette wheel selection with replacement ). Selected genomes were paired to conduct a crossing over with a probability of 0.005. The resulting genomes were subjected to mutation (probability of 0.005 per bit; i.e., 0.04 per gene). This process of selection, recombination, and mutation was repeated until there were enough genomes for the 1,600 individuals (200 groups) of the next generation. The level of altruism was calculated for each group as the proportion of collected food items that was shared within a group: A = n(a)/(n(a) + n(s)), where n(a) was the number of collected food items individuals shared and n(s) the number of items individuals did not share. Source
I have been a programmer for almost a decade and I understand how programming works, and how it cannot work.
You are still proving the point, that these robots did not get this ability naturally, but it was consciously designed.
But many of us believe the trait must have originated, like all others, in a random mutation.
If the menu had been randomly assembled and contained the same traits, the result would have been the same.
I'm not saying that altruism cannot result from random mutation, I am saying that THIS experiment is not random mutation.
This experiment is completely rigged up with Hamilton's rule and a few oddball numbers.
Glad to see you've finally seen it my way.
If you read through my postings carefully, you will understand that my points are right about this article.
One thing is brought up... why isn't there any source code?
One of the comments in that site is why the need of robots? Why couldn't it be simulated in computers? (ie MATHLAB).
They have done this before... like for example Conway's Game of Life.