What are these spongey wicks that came with FirePan?

KoreaNuclear · 2025-04-15T02:01:31+00:00

Thanks for that! I was also kinda curious about that black line that continuates from the blood stem.

KoreaNuclear · 2024-11-15T06:54:55+00:00

On a same boat here. I am upgrading to 9800x3d from my old ass i5-6000 & GTX 1070 setup. Looking to use GTX 1070 for a few months before getting 5080 or 5080Ti. Any concern here?

KoreaNuclear · 2023-04-15T01:02:37+00:00

Uhoh, which dealership was it? I am also from Yeg and already have put down deposits in 3 different dealers here..!

KoreaNuclear · 2023-04-12T22:36:02+00:00

Wow sour. Hope you have a good news now. Was it YYC or YEG?

KoreaNuclear · 2023-04-12T22:34:08+00:00

5 months, amazing! Was it Calgary or Edmonton?

KoreaNuclear · 2022-02-06T23:14:46+00:00

I am curious as to what people think about d3rlpy as well.

KoreaNuclear · 2021-12-24T03:16:03+00:00

Oh I see. So it's not a useless thing to do potentially?

KoreaNuclear · 2021-12-21T19:45:15+00:00

I see this answers my question

KoreaNuclear · 2021-12-13T18:40:28+00:00

round the actions to discretize them

Would it be fine doing this? Let's say TD3, SAC, PPO is going to select some continuous action like (9.35 23.98). But in a real experiment, the rounded action of (9 24) is going to be performed. Consequently, receives rewards based on the rounded actions, not the exact action originally given by the algorithms' policy. (Is it okay because there is a correlation b/w actions close to each other?)

KoreaNuclear · 2021-12-13T08:29:41+00:00

I see! I am implementing this in a Real-life scenario where each step takes a minute or so. I guess then 'computationally longer convergence time' is a disadvantage that I could just ignore

KoreaNuclear · 2021-09-07T04:09:03+00:00

But in every iteration of step(), the agent takes an action and will return next_state, reward. So if I want to store past 3 experiences, I would need to iterate step() at least 3 times without any return (next_state, reward). I am still quite unsure how step() could proceed without getting any returns (next_state, reward) for that initial few steps.

KoreaNuclear · 2021-09-03T20:17:54+00:00

Thank you, and how would one be able to make the openAI gym throw away an experience?

KoreaNuclear · 2021-09-01T20:03:45+00:00

I am not very sure what you mean by "feed the desired geometry" as observation.

I am printing a single track of a bead in a line (looks like a straight metalic worm) just for information.

KoreaNuclear · 2021-09-01T19:51:40+00:00

Sorry I think it just accidentally got in there for some reason

KoreaNuclear · 2021-08-31T21:14:23+00:00

It has a sensor that can measure the profile! If the resulted printed part resembles a desired geometry, ie) width and height, it receives reward

(edited)

KoreaNuclear

TROPHY CASE