What's the highest ranking non-learning bot in the rumble?

This is pretty much what I had in mind, particularly "similar states give similar decisions". Another distinction I find helpful is the idea that past results should not influence decisions in the future but past states can. A gun that gathers statistics on hit/miss and adjusts its aim is learning but average velocity targeting is not.

If average velocity (with window size k) is non-learning, how about play it forward using only k recent scans? Both are not changing behavior based on results, only recent scans, plus, play it forward is merely a more precise version of “averageing”.

IMO both are learning using k scans, the only difference is the latter is more precise, and using data more effectively.

I definitely agree that they're both learning, at least in some sense. The main difference is that the accuracy of a linear targeting system would have diminishing returns as k is increased, whereas a PIF system would likely benefit from increased amounts of data.

It's certainly a difficult question to formalise. I suppose that plotting prediction accuracy vs. k would give some idea of how much learning is going on.