A CLI was released and a report of some insights from the results it generated should be coming later today (out now, link)
The more I look into it the more I feel there is really limited ways I can improve the sampling, and they all require massive code changes and I need a break before working on this for another month.
That said I’m really glad how this turned out, the original ML model does very poorly in terms of evaluating each branch. Something I’ve been thinking about is, out of 100 marks of making a stronghold nav AI, 40 is for evaluating leaf nodes and 60 is for the agent policy, the original model gets something like a 20/40 for the former and 40/60 for the latter. But I know in my heart that I’m not satisfied with either of those, now with this generator I would say it is able to score at least 35/40 for evaluating leaf nodes, the 5 points for not being effective enough for really bad strongholds but still for the ones that it is effective enough it is the best possible solution that no machine learning model can reach with any amount of training.
What really interests me in this project is that it provides endless things to learn and math problems to solve and I really enjoy that.