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There are a few things that are assumed to be true when talking about the Pareto frontier here, but aren’t always true. One, that more of something is always b
by cortesoft 2mo ago
There are a few things that are assumed to be true when talking about the Pareto frontier here, but aren’t always true.
One, that more of something is always better, e.g. it is always better to have more speed.
Maybe, but what if having too much speed causes you to run off the track and perform worse? It could be that there is actually a peak in the utility of speed that declines as it increases.
There could also be important relations between attributes that make determining a Pareto frontier impossible or at least more difficult. For example, some pairs of attributes work best when they are a specific ratio, and increasing one or the other will actually decrease utility unless the other is increased at the same time.
- Barbing 2mo ago> [is it really] always better to have more speed[?] I'm reminded of two things that in a way support your premise with the second example being more relevant. Both are outside what’s being discussed exactly, more about knock-on effects maybe, anyway: The first is that Angry Birds found the speed of launching birds into structures was important for engagement: it cannot be too fast. The second is from a commenter somewhere who said they had or worked on software that took ten minutes to boot in the morning, which is when employees made coffee and talked and brainstormed. Everyone was disappointed when after refactoring, the software booted immediately.
- dfdydx 2mo agoWouldn't that just change the shape of the pareto frontier? It stops at some point (when marginal utility becomes negative) - but this is not special, they typically stop at 0 as well.
- cfiggers 2mo agoOne way of defining Wisdom is the ability to look at a set of metrics and discern when an adjustment or adaptation to them is needed in order to better approach the true objective we are optimizing toward—since the true objective is almost never perfectly described by any of the metrics that we can find to approximate it. Eventually, almost every attribute we can practically and objectively measure is at best a proxy measure for the thing we actually want to know, which is, in this case, "Most likely to win races." The thing we actually want to measure is often hard, impossible, or impractical to objectively measure, which is why we resort to proxies in the first place. By "proxy measure" we mean, not a perfect 1:1 to the thing we want to measure, but containing some amount of signal about it. So yes, sometimes there's a peak in the utility of speed. But perhaps that trade-off can be modeled by another attribute called "Proneness to fly off the track" which increases as speed does, and is weighted such that the peak and then taper-off of benefit in speed is captured between the combination of the two of them. But then, any vehicle that has the same speed but lower "Proneness to fly off the track" would be objectively preferable to any equally-fast vehicle with greater "Proneness to fly off the track." And so it continues.
- Shocka1 2mo agoI agree that many assumptions are made, but the concept was presented well in combination with something most people can relate to. They mention in the Acknowledgements section at the end of the post that assumptions are made, but not sure if they added it after your post or not. When something goes viral on HN authors tends to add things... I think to truly do a deep dive into the best overall character in Mario Kart would be a fairly complex task. We'd need data from years of real games and players to even get started. As an ML engineer/software engineer who played a lot of Mario Kart back in the day, this post was a very enjoyable read for me.