A fairly similar statement holds for practically all game playing algorithms; in this respect, chess differs little from go, even though the algorithms used to solve each tend to be quite different. However, the story changes when we move to AI planning algorithms more generally; backchaining is common for planning.
I think studying AI algorithms for these sorts of things is, generally, quite informative with respect to what types of reasoning you can expect to work well. Especially if you then practice the skill yourself and watch for what kinds of reasoning you’re doing, and when they’re effective.
A fairly similar statement holds for practically all game playing algorithms; in this respect, chess differs little from go, even though the algorithms used to solve each tend to be quite different. However, the story changes when we move to AI planning algorithms more generally; backchaining is common for planning.
I think studying AI algorithms for these sorts of things is, generally, quite informative with respect to what types of reasoning you can expect to work well. Especially if you then practice the skill yourself and watch for what kinds of reasoning you’re doing, and when they’re effective.
Interesting suggestion! Is there a starting point you would recommend for this sort of study?