Does anyone know of applications/variations of Simulated annealing (or similar search strategies) where the search space is dynamic, i.e. changes over time between iterations ("generations" in genetic algorithms)? Like travelling salesman but the roads keep changing.
Maybe there's no fundamental change required? Just keep searching for better solutions and possibly accept worse ones with some probability, even if the space changes? The problem I'm seeing in my area is defining the neighborhood function when possible paths change over time.
@bjoreman very much correct. Yeah, we should set something up! DM? :)
@ptitfred It's built with Kotlin for backend services and web server, and HTMX on the frontend.
Currently building https://squidler.io/, and I haven't had this fun programming in a long time!
@larsrh 😍
@lucifargundam linear temporal logic
@bjoreman nice!
@bjoreman did you meet some of my IKEA colleagues? ☺️
# Quickstrom 0.5.0 is released! 🎉
It's an entirely new implementation, with a new specification language (Specstrom) and underlying logic (QuickLTL). Browser testing reimagined!
**Docs:** https://docs.quickstrom.io/en/0.5.0/
**Source:** https://github.com/quickstrom/quickstrom
I know I'm annoying. It's just been so quiet for so long. I've mostly focused on research and applying it in work situations. This release feels scary but I'm really looking forward to it getting even more industry usage (hopefully!)
@rosactrl I've still not made the jump, although I've tried it a couple of times. Not being able to pass parameters into flakes has been sort of a show stopper in those cases. Not sure if I should just work around that, if it's worth it. I'll probably wait for flakes to be considered stable, although that might not be soon? I have no idea, really....
@acowley absolutely wild!
@jstepien yes! ❤️ And old friends are popping up everywhere. It might actually work this time...
@quinn feels good without the straightjacket, for sure!