Crossover2 and weightmapping #1
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Crossover 2 takes a random city and finds it's position in the parent's order vector, then choses one parent randomly but weighted based on their performance and places thic city in the output vector in this position. If the first choice parent's position is taken alread the second choice is used, if both are taken it is placed randomly at the end. Mutations prevent the whole population becoming identical and introduce new samples occasionall. Works well with weightmapping - replaces crossover in sketch.
the whole population is displayed at once in the upper figure. The thickness of the lines are proportional to how many networks take that route. Making it easy to see if the population is evolving or randomly guessing.
Mutate function wasn't running in DNA but works in skech, more features have been added and some values fiddled.
Mutate was being called but not returning a value, ultimately leading to crasthes but more annoyingly not actually modifying the order. also now every1000 generations there are 5 generataions of extream mutation to help keep things progressing. The best ever is always in the population now also
used the wrong variable name in one place
Added 10000th roor parenting this very mild bias towards the better parent means slightly inefficent networks can form a breeding population allowing improvements which require muliple mutations to be found - anything is better than equal parenting however. apocalypse spelling correction... and happens more often with more mutations but is shorter. Maximum stack exceeded error prevented (was low probability) Now 'solves' for 50 cities in about 5 minutes
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New crossover technique which leads to a closer relation to actual evolution (whole population converges) , weightmapping diagram shows this nicely.