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View Code? Open in Web Editor NEWA tool that evolves small brains capable of scanning and classifying an image.
License: MIT License
A tool that evolves small brains capable of scanning and classifying an image.
License: MIT License
e.g. in http://eplex.cs.ucf.edu/papers/morse_gecco16.pdf
Greg & Ken only evaluated 2 instances per individual per generation and found that the GA still worked well if the individuals inherited their parents' fitness.
Instead of only considering the ACC's outputs at the very end of the simulation, we can sum the ACC's outputs over the time series to calculate the "confidence" that the ACC thinks that the image belongs to each class. In simple mathematical terms:
Confidence_i = sum(NumStepsGuessed_i) / TotalNumStepsInSimulation
Thus the ACC can modify its confidence in the image belonging to a certain class over time. This might be useful in cases where an image can potentially belong to multiple classes.
Perhaps binarizing continuous inputs is losing important information for the ACC. Might be worthwhile to try out NEAT.
It could be useful to encourage the ACCs to explore more of the image via some form of novelty search. e.g., one of the objectives could be to view as many pixels as possible.
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