HackerReposA FIELD GUIDE TO OPEN SOURCE
ProSponsor the shelf♧ 0
← Back to top all-time
Farama-Foundation
ViZDoom
C++2016–2024
Farama-Foundation / ViZDoom

ViZDoom

Reinforcement Learning environments based on the 1993 game Doom :godmode:

3Distinct people
3Mentions
0Explicit recommenders
2.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Reinforcement Learning environments based on the 1993 game Doom :godmode:

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year3 dated mentions

Observed mentions: 2016-04-22 12:48:31 UTC to 2024-08-28 08:43:23 UTC.

0122016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC202
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

3 sources
Doom system requirements: - 4 MB RAM - 12 MB disk space Stable diffusion v1 > 860M UNet and CLIP ViT-L/14 (540M) Checkpoint size: 4.27 Gb 7.7 GB (full EMA) Running on a TPU-v5e Peak compute per chip (bf16) 197 TFLOPs Peak compute per chip (Int8) 393 TFLOPs HBM2 capacity and bandwidth 16 GB, 819 GBps Interchip Interconnect BW 1600 Gbps This is quite impressive, especially considering the speed. But there's still a ton of room for improvement. It seems it didn't even memorize the game despite having the capacity to do so hundreds of times over. So we definitely have lots of room for optimization methods. Though who knows how such things would affect existing tech since the goal here is to memorize. What's also interesting about this work is it's basically saying you can rip a game if you're willing
Read the rest
to "play" (automate) it enough times and spend a lot more on storage and compute. I'm curious what the comparison in cost and time would be if you hired an engineer to reverse engineer Doom (how much prior knowledge do they get considering pertained models and visdoom environment. Was doom source code in T5? And which vit checkpoint was used? I can't keep track of Google vit checkpoints). I would love to see the checkpoint of this model. I think people would find some really interesting stuff taking it apart. - https://www.reddit.com/r/gaming/comments/a4yi5t/original_doo... - https://huggingface.co/CompVis/stable-diffusion-v-1-4-origin... - https://cloud.google.com/tpu/docs/v5e - https://github.com/Farama-Foundation/ViZDoom - https://zdoom.org/index
In Diffusion models are real-time game engines
> The doom maps are almost all completely dull looking and gray I will fight you ;-) But seriously: The project uses a source port of Doom[1] based on ZDoom[2] which supports high screen and texture resolutions, mouse look, colored lights etc. Although I think that since Doom has less visual clutter (bloom, shadows, ambient occlusion, screen distortion) than a modern AAA game its display should be easier to read. [1] https://github.com/Marqt/ViZDoom [2] http://zdoom.org/About
In Visual Doom AI Competition

MAKE YOURSELF AT HOME

A few shortcuts

/
Search the collection
?
Open this guide
Esc
Close dialogs and navigation

Your saved repositories and interests stay in this browser.