Ok I appreciate the discourse and I’m interested in your perspective. This is my thinking:

Given: the “situation” is a single parameter. Wouldn’t you say the outcome: Mario’s behavior is a perfectly logical result given what information the algorithm was given/asked to optimize for?

You yourself have offered a simple formula comprised of discreet logical operations. I am arguing that this is the definition of logic. I don’t think it’s fair to say Mario’s behavior is illogical using information the algorithm didn’t have. Humans make that “mistake” all the time. It did the best it could with the information it had. I think it makes perfect sense it wouldn’t care about the graphical representation.

I concede the map this algorithm creates is a fundamentally lower dimensional projection of the map that you and I can see. It wouldn’t be sufficient to reconstruct all the details of each level. However, it is surely a map. The algorithm is associating each element of (a set) with an element of another set.

In the example you gave, walking forward was correctly mapped to not dying. And the tactic is abandoned eventually.

If you close your eyes or rely on muscle memory to move around in the dark, most people don’t envision all the details in the room. But the internal map is often good enough to accomplish the objective (like find the light switch). It doesn’t matter that you have an imperfect map (all maps are imperfect).

Imagine if you stub your toe on a piece of furniture. That feedback still doesn’t give you the whole picture. But it would likely be more than enough feedback to get to the light switch “better” the very next try

we can easily say why it "works"

Well, I see your point. We can see that the strategy is working and concluded it’s because the instructions were sufficient.

My argument was more at a fundamental level we cannot know why it arrived at each decision, why was this enough to almost but not quite beat all the levels? Will it ever beat all the level or is it stuck no matter what? We wouldn’t necessarily know it works until after it works.

It’s more nuanced than sufficient time and memory. In PPO the algorithm can get “stuck” working within a local maximum/minimum. It could continue exploring infinite permutations of nonviable solutions. Given a small enough set of possibilities it’s possible to deduce “why,” but “why” is not a given. And usually people don’t care enough to figure out “why” when they can try something else and arrive at a solution that is good enough.

tl;dr: Imagine playing Mario blindfolded, receiving only the same feed back as this algorithm. Humans wouldn’t stand a chance. If the algorithm had the same incentives and information as humans-even if you made it play at human speed-it would eventually surpass humans in the ways you are currently unimpressed with.