Analysis of komi values for increasing Go board sizes and agents strength
From my experience of solving some other games, usually there is a huge difference between optimal player and an average player or even state-of-the-art engine. I bet the results for any other player then optimal will diverge from the results of optimal play. For example see what happened with some famous chess positions when endgame tables where developed (see Tablebases, Fermat, Knights and Knightmares - you might need access to ICGA Journal). Optimal solutions frequently destroy any intuition about a game. I expect that even AlphaGo Zero approach would be not enough even for small boards like 7x7 to approximate the optimal komi value.