[SamBam]

Evolution works in an incredibly complex "fitness landscape," where certain minor tweaks in phenotype or behaviors can affect your fitness in quite complex ways.

Genetic Algorithms attempt to use this same system over extremely simple "fitness landscapes," where the fitness of an agent is defined by programmers using some simple mathematical formula or something.

When the fitness function is being defined in the system by programmers, instead of emerging from a rich and complex ecosystem, then the outcome depends exactly on what the programers choose. If they fail to see the consequences of their scoring algorithm, that's on them. There's nothing really magical going on, they simply failed to foresee the consequences of their choice.

(As someone who has worked with GAs and agent models, this outcome really doesn't surprise me. I would have said "oops, I need to weight the time less" and re-run it, and not thought twice.)

[mcguire]

From the article: (I don't know Chinese, but the animations are clear enough.)

https://www.bilibili.com/video/BV16X4y1V7Yu?p=1&share_medium...