Vlad-Shcherbina / icfpc2018-tbd

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Implement default strategy and then optimize it #4

Open manpages opened 6 years ago

manpages commented 6 years ago

This is all about getting our feet wet with the actual solvers. We want to have a good baseline solver that performs marginally better than default strategy. Hopefully, learning tricks like when to Flip, at the very least.

kevroletin commented 6 years ago

I think there are several optimizations to the default approach:

kevroletin commented 6 years ago

Current progress: there is a (seemingly) working default solver. It was checked on several tasks using the online visualization tool.

kevroletin commented 6 years ago

We've adapted production/pyjs_emulator/run.py to test the solution. We've discovered several failures on first 20 test and investigating where is the problem.

ixahedron commented 6 years ago

So the default solver now finally behaves like a proper default solver and is marginally optimised on top of that, by just returning to 0 faster (in 15-decrement steps) after filling in all the needed voxels. @kevroletin and I continue working on it.

manpages commented 6 years ago

@kevroletin what is the status of this issue?

kevroletin commented 6 years ago

AFAIU ixahedron wants to improve it so default strategy can be used as a library function in other solvers.

kevroletin commented 6 years ago

I did "improve bounding box approach by computing bounds for each layer or better for each line" (but, unfortunately as a separate implementation default_solver2.py). It takes a working rectangle as a parameter, so it can be used as a building block for other solvers.

kevroletin commented 6 years ago

Also parallelized to 4 robots. Going to add deconstruction phase and turns the solver into a full solver.

ixahedron commented 6 years ago

Default solver (v1.4) works for all problem types, but no further improvements were introduced. Will focus on integraring @kevroletin 's work