Just checking if I understood your argument: is the general point that an algorithm that can think about literally everything is simpler and therefore easier to make or evolve than an algorithm that can think about literally everything except for itself and how other agents perceive it?
I’d go a bit farther and say it’s easier to develop an algorithm that can think about literally everything than one that can think about roughly half of things. That’s because the easiest general intelligence algorithms are about learning and reasoning, which apply to everything.
Just checking if I understood your argument: is the general point that an algorithm that can think about literally everything is simpler and therefore easier to make or evolve than an algorithm that can think about literally everything except for itself and how other agents perceive it?
Exactly.
I’d go a bit farther and say it’s easier to develop an algorithm that can think about literally everything than one that can think about roughly half of things. That’s because the easiest general intelligence algorithms are about learning and reasoning, which apply to everything.