TLDR: I have an asymmetric evaluation function for an implementation of negamax - is that acceptable? Or do I need to make it symmetric?
Longer: I'm writing a game AI (for the chess-like board game "Hive") that was using minimax with alpha-beta pruning and an asymmetric evaluation function.
But I was having trouble adding transposition tables correctly, and was losing confidence in my minimax implementation, so I decided to switch to negamax using the pseudo-code here: https://en.wikipedia.org/wiki/Negamax#Negamax_with_alpha_beta_pruning_and_transposition_tables
I've got everything "working" and AFAIK accurately following the pseudo-code, but my AI is now making some wildly different moves than before and games that usually ended after 10-15 turns now take 30+, and I'm not convinced the AI is actually playing better than it was before. I'm worried that having an asymmetric evaluation function means I'm scoring nodes differently than before (because of the negamax flip-flopping).
I don't want to change to a symmetric function unless I really have to - I've been trying to produce an optimal function experimentally (AI vs AI battles) and have put in hundreds if not thousands of compute hours into producing a strong evaluation function.