Used gradient boosting as a surrogate model + genetic search
Miners sent 6
Smiths sent 2
Woodcutters sent 0
Farmers sent 1
Brewers sent 2
Warriors sent 1
Crafters sent 1
https://github.com/alex-ledovsky/my-notebooks/blob/master/Dwarves%20and%20Data%20Science.ipynb
Condition applied - Farmers + Brewers >= 3 (survivability = 99%)
Hi, guys! I'm kind of new here =)
Did I understand the problem right? I understood the problem as "Build an algorithm which finds the best distribution of 13 dwarves in order to get maximum expected fort value"
I looked through the solutions of others and saw mostly insights from the data. Was I right to apply ML/optimization? I mean, no one else did anything similar and maybe I understood the problem wrong... (maybe the problem is to understand and explain how the game works or smth else)