(Ab)using general search algorithms on dynamic optimization problems (2023) (dubovik.eu)
I wrote this blog back in 2023 but since then I became a frequent lurker on HN and decided to repost the blog here. For me, writing it was about connecting the dots between dynamic optimization techniques I've studied as an economist and the more general search algorithms studied in CS.
8 comments
[ 2.9 ms ] story [ 22.7 ms ] threadYou can just take Show HN out of the title, though or repost without it.
This never took off. I don't if it didn't work or it was a matter of the "bitter lesson" ideology pushing people to prefer hardware acceleration over smart algorithms. I would note that smart algorithms require hiring (more)smart people and not only can hardware acceleration be cheaper but hardware and data can be more reliably added than smart people, who are short supply.
[1]: https://arxiv.org/abs/1903.03129
Any ideas as to why? Also missing "in" hope you can edit this because that's a nice quote.
The rest of the pipeline was straightforward. I exported individual frames in a .ppm format, which was easiest to program, and then stitched them into an .apng animation using ffmpeg. Did quite a few tests initially to choose between .apng and .webp and back then .apng was least glitchy across the devices I have.