Certainly believable in that these approaches approximate many real-human strategies, but I’m not sure it’s clear that it’s a useful metaphor for more complicated, difficult-to-video-and-analyze situations. I also suspect that even Robert would fail most of the time, just due to setup variance (slight differences in flex, slight differences in trajectory down the track, differences in other environmental factors, all of which lead to enough difference in off-track trajectory to miss fairly often.
You also didn’t specify budget and payoff/cost, which would have a HUGE impact on what equipment the experimenters invest in, and how much effort they put into obvious things (like, say, asking for outside advice (or even setting up multiple teams and an internal prediction market) on how to solve, rather than doing it in a vacuum).
Certainly believable in that these approaches approximate many real-human strategies, but I’m not sure it’s clear that it’s a useful metaphor for more complicated, difficult-to-video-and-analyze situations. I also suspect that even Robert would fail most of the time, just due to setup variance (slight differences in flex, slight differences in trajectory down the track, differences in other environmental factors, all of which lead to enough difference in off-track trajectory to miss fairly often.
You also didn’t specify budget and payoff/cost, which would have a HUGE impact on what equipment the experimenters invest in, and how much effort they put into obvious things (like, say, asking for outside advice (or even setting up multiple teams and an internal prediction market) on how to solve, rather than doing it in a vacuum).