Tommy Markstein

I have the same behaviour not just in VSCode 1.47.3/v2020.7.96456 but also in PyCharm 2020.2 with Python 3.7.7

Is your environment always the same on every run or is slightly randomised? It could be that your best species just "had a bad day" on particular environment config (like...

> This seems like a feature, I didn't make this library but read about the mechanisms used for evolution. Sometimes neurons get isolated or replaced at random, this includes disabling...

I created a fork that has a changed implementation. It will remove all dangling nodes and connection at the end of every run If people wanna try it out: https://github.com/markste-in/neat-python/tree/remove_dangling_nodes...

Maybe it would be easier to make “calculate_driver_ahead“ function separate. Then it won’t impact the functionality of other functions and can still be called independently if needed

Follow up: https://github.com/CodeReclaimers/neat-python/pull/274

Yeah exactly. In most of cases that I tested the algorithm got stuck because most of its "brain" was "dead" (dangling nodes without any impact). Further evolutions just made it...

I forked the project and in the **branch "remove_dangling_nodes"** I now have the option `trim_dangling_after_n_generations_wo_improvment` in the config file. If you set it to anything greater 0 it will trim...

I also found out that sometimes the output of an network are mistakenly used as an input. I fixed that in the my branch too. 

ah nice but it looks like u remove potential dangling nodes directly. I am curious if it might be helpful to keep them for a while. Like I leave them...