Open tylertownsend opened 4 years ago
Ideally distance is a measure of dissimilarity between the AGraphs. It was implemented in the current way mainly based on a need for fast evaluation. We could try a different (and likely slower) implementation and see if the reduction in evaluation speed is made up in quicker evolutionary convergence.
I just read a paper on alternative, hash-based distance metric: https://arxiv.org/abs/1902.00882 this could be worth implementing and comparing
The Distance function compares row-wise for each element to see if they match. However, how does this reflect to AGraphs with the same equation tree, but with different command arrays. For example let,
and
And
distance(command_array_1, command_array_2) = 8
since the first row is the same, and the 0 in the 1st column-index of the 2nd row-index is in both arrays. However they both describe an equationf(x) = c_0 * x_0
. Should the distance reflect the AGraphs or the command arrays?