Earlier quoted context omitted.
The page says: > For better results, increase the population size to 500-1000 and wait for 50-100 generations Do you have example output from that? I'd expect my computer to take months of running 24/7 to get there.
Yes, you may press the "Restore Evolution" button (at the bottom of the screen) and then upload the pre-saved training checkpoints from here https://github.com/trekhleb/self-parking-car-evolution/tree/... You may also press the "Restore Evolution" button and then press "Use demo checkpoint" to use some pre-trained data.
Show HN: Self-Parking Car Evolution
31–40 of 45 posts
Re: Show HN: Self-Parking Car Evolution
#32https://www.kaggle.com/c/abstraction-and-reasoning-challenge
Re: Show HN: Self-Parking Car Evolution
#33How challenging would it be to design something similar generically, such that you can just define the "pain" and "reward" and just have some random 3D model in a 3D world take random actions until there's no more "pain"?
Re: Show HN: Self-Parking Car Evolution
#34How challenging would it be to design something similar generically, such that you can just define the "pain" and "reward" and just have some random 3D model in a 3D world take random actions until there's no more "pain"?
What your describing is reinforcement learning :)
Re: Show HN: Self-Parking Car Evolution
#35Really enjoyed this bug haha: https://github.com/trekhleb/self-parking-car-evolution/issue... Auto manufacturers should just implement that behavior!
Re: Show HN: Self-Parking Car Evolution
#36Re: Show HN: Self-Parking Car Evolution
#37> Whenever the sensor doesn't see any obstacles it reports the value of 0. On the contrary, if the value of the sensor is small but not zero (i.e. 0.01m) it would mean that the obstacle is close. I would guess that mapping ”nothing here” to a value that is higher than the others would give better results. The software wouldn’t have to learn that weird inversion where the safest value is very close to the least safe o…
Alternatively, it would be interesting to try having the sensors output 1/(distance + k), where k is maybe 0.1m. Then the output would naturally go to zero as things got further away.
Re: Show HN: Self-Parking Car Evolution
#38Earlier quoted context omitted.
The page says: > For better results, increase the population size to 500-1000 and wait for 50-100 generations Do you have example output from that? I'd expect my computer to take months of running 24/7 to get there.
Yes, you may press the "Restore Evolution" button (at the bottom of the screen) and then upload the pre-saved training checkpoints from here https://github.com/trekhleb/self-parking-car-evolution/tree/... You may also press the "Restore Evolution" button and then press "Use demo checkpoint" to use some pre-trained data.
Re: Show HN: Self-Parking Car Evolution
#39Earlier quoted context omitted.
Have you thought about a native version? I get the appeal of writing for the browser but it's so damned slow compared to what you could get natively.
I haven’t thought about the native version, it was fun trying to implement it for browser. To resolve the performance issue I would try next to switch to the 2D simulation engine, since we don’t use the height during the parking. Getting rid of the 3rd dimension, lights and complex geometry would increase the performance drastically I believe
Re: Show HN: Self-Parking Car Evolution
#40I've got "Component has crashed" on mobile Firefox, not very optimistic :)