I'd imagine it's solvable by just about everything. This is one of those cases where the core problem isn't that the problem is hard, it is that it is so easy that it is a challenge to get humans to even perceive it as a problem on such a small scale. Any planning system will hit something like this all but immediately.

I'd say a lot of the earliest AI optimism was a failure to understand just how hard things that in the simplest case are so simple we don't even perceive them as problems in the first place. For a much more complicated example, I doubt anyone in 1970 would imagine that in 2018 we're still trying to get robots to walk from here to there. (Yes, lots of progress has been made, but it's still very much cutting edge, a research project, and a bespoke one-off effort each time, not a "Oh, I'll just swing on down to the robot store and pick up a walking chassis".) We don't see it as a challenge because for our conscious minds, by the time we're old enough to be doing robotics research, it's zero cognitive effort for us.

This solves the problem by searching the graph of reachable states (and presumably doing cycle detection, at least in depth-first mode), which avoids the problem of picking an unsuitable sub-goal by considering all possible ones. While this is a perfectly good solution, it doesn't seem to throw much light on how human intelligence works. A person is likely to notice, for example, that extending any stack that does not have C on the bottom is not helpful, without mentally running through all possibilities, but just on the basis that it will have to be torn down at some point, to move the bottom block to where it belongs.

Are there any unsolved/unsolvable anomalies similar to this one?