> you can't be trapped in a sub-optimal situation and be rational at the same time.

In order for this statement to be true, you must also have perfect knowledge: something that is unachievable in most circumstances. Getting trapped in a local-optimal solution is perfectly possible if you are blindly following stochastic decent along a gradient: as it is too with life... getting trapped like this looks like being in the situation where there is no rational action (only irrational ones) that (eventually) lead to anything other that that status quo. a local optimum is where you have to do increasingly (in proportion to the level of optimization) non-positive actions to escape (likely to another local-optimal).

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pasquinelli a day ago | parent [-]

> In order for this statement to be true, you must also have perfect knowledge: something that is unachievable in most circumstances.

if the optimal situation requires perfect knowledge that can't be had then it's not the optimal situation, it's a fantasy. it's like saying the fastest route through a maze is a straight line from the start to the finish-- that would be true if the maze wasn't there.

there are two ends to what i'm arguing but people seem to only be able to hold one in their mind at a time.

	▲	altruios 13 hours ago \| parent [-]
		okay: I have to generous with your diction and your intentions. I believe you are trying to say that since 'optimal algorithms for choices exist': 'local maximums can't exist'. It is very possible to have a optimal algorithm that leads to a sub-optimal (local maximum) because the problem is np hard. Both in math and in life. "It is possible to commit no mistakes and still lose. That is not a weakness. That is life" - Picard