[gwern]

> Ideally, I'd like to continue working on it to build something that can help clubs make minimal, inexpensive changes while maximally improving the strategic interest if the way the course plays.

Yes, that's why I mentioned that this gives you at least one possible measure of 'strategicness' which can be computed automatically. Measure the variance across policies (skill level, which maybe you could define physically as some sort of 'mean absolute circular error' in strokes?), and now you can do quite simple optimization routines to modify courses. Like take a course, randomly flip some squares to sand/water/grass/etc, compute the new strategicness, and keep it if it's higher. Random search, simulated annealing, CMA-ES, novelty search, lots of easy possibilities I bet even a LLM could implement for you these days which would let you take an existing golf course and search for new modified layouts with higher strategy, to inspire a human expert in modifying a course.

[scoofy]

>Like take a course, randomly flip some squares to sand/water/grass/etc, compute the new strategicness, and keep it if it's higher.

Holy crap, this is a really good idea. I’ve already shown how this is done by adding and removing bunkers, but single pixels is extremely smart.

>would let you take an existing golf course and search for new modified layouts with higher strategy, to inspire a human expert in modifying a course.

I’ve seen so many folks misunderstand what I’m doing here. I applaud you here. Finding the minimum viable (cheapest) way to improve the strategic elements of a golf course across handicaps is more important than ever, and is one of the goals of this exercise as a potential product.