Nixx

Thank you for your feedback 👍 I had the same thought about the cyberdemon at the end. I wanted to create an end of map with a bit of challenge. Maybe I didn't do it the right way

I thought about it, but the problem is that nothing indicates, apart from the .txt, for which source port the wad is designed. And the idgames API does not distinguish between a wad intended for Doom, GZDoom, MBF, Boom etc. In summary, it is possible if the source port is GZDoom, which supports all formats. Afterwards I must manage so that the files are executed in the right order. In theory this is possible to determine, with a system that analyzes the files and determines which source ports are compatible. But you will understand that this project is done in just an hour or two. If someone with the motivation and skills wants these features, they can always submit a pull request or fork their own downloader

Hi Tired of endlessly searching for a wad to play? And what Endless Random /idgames WAD Adventures doesn't suit you? I present to you THE solution to your problem: the random wad downloader, an idiotic project, not neat and barely tested allowing you, as its name suggests, to offer you a wad randomly on IdGames, to download it, or not. I apologize in advance if the topic is in the wrong place. Test it => Releases · Nixx57/IdGamesRandomDownloader (github.com)

Thank you =) Looking forward to seeing the full gameplay, it's always interesting to see how players play our maps. Sometimes it pushes us to rethink certain designs because often, things happen that weren't designed like that. For example, the eye in the wall "sigil style" seemed to me to be easy to find.

Good news, this new source port in C#, and the architecture seems excellent to me from what I have seen, there is managed-doom which I had the opportunity to tinker with a little. Looking forward to taking a closer look EDIT : my bad, I hadn't seen that its first version was from a year ago, definitely, so many things that you don't see if you don't look a little

Hi @sponge @Edward850 (others here?) Is the Unity port still in active development? I had bugs to report to the team, such as the exit message, in Italian in the French version, or a bug that occurred in the key binding menu. I tried to go through the classic procedure: open a support ticket, but I was kindly told to update my drivers and restart my PC...

Thank you very much for your very complete feedback, the mappers are happy to have feedback on their maps. As for pain elementals not spitting lost souls on map 14, thank you for this feedback, it may be a problem specific to GZDoom, no one has noticed this problem so far, it works of course DSDA and Crispy. I will test for my part to see if it is possible to correct without breaking everything.

Among those who played wad, did you notice any problems? Any inconsistencies or anything that will help us perfect the final version? Your feedback will be welcome

@Vile streamed the wad, I watched the replay to see how he was doing (too well) and to know the first hot feedback on my maps (10 and 14): he speaks too fast and me not being a native English speaker, it was difficult, but overall I think he enjoyed it, so I'm happy for my first maps created and published Thx for playing it @Vile :) Looking forward to seeing the end

Hi I've heard that there can be performance issues on large maps (especially MAP02). It is possible that this is due to the use of a GZDoom type sourceport or derived with OpenGL. Try with an optimized sourceport like PrBoom+/DSDA or CrispyDoom, it is mainly with these that the maps have been tested.

Hello everyone, It's time to give some news after all this time: To date, all maps are completed and tested internally. There are still the final finishing touches to be done before we finally invite you to play it. Beta/Release (to be define) very soon The Flesharmonic team

Yes, I use shotgun if weak enemies are partially protected by an obstacle (a small wall for example), it is more optimized thanks to horizontal dispersion only, as well as in other situations where horizontal dispersion gives an advantage or to kill weak enemies (imp and hitscanner)

Yes, from what I have read, this way of proceeding looks like supervised learning, even semi-supervised. Ideally, I think unsupervised learning is best, with the goal of reaching the end-of-level switch, and can also increase its score with 100% kills and secrets. As for Autodoom, I hope that @printz will get back to it soon to implement jumps and optimize its node builder (the bot tends to follow edges sometimes and fall in a loop), as well as being able to support limit removing maps, because the maps I create crash on startup, but I think it comes from my nodebuilder (ZDBSP - UDMF). But he still did a great job so far, if he improves it, I'll use it as a testing tool, by the way, I recorded a title screen demo for the wad I'm working on with other people, we'll see if we use it.

Hey, New screen: Look familiar? By DataCore:

Hello, Sorry to resurrect this thread, but the subject interests me and I've been looking into it in a concrete way, it seemed silly to open a thread just for the following: I made a quick little project that collects data at each tick and saves it in a CSV, whether it came from a demo, launched instantly (as fast as the CPU can) and without visuals or launched normally, I was able to recover everything: positions of vertices, linedefs, sectors and the height of the floor and ceiling, everything relating to "things", position, health, "frame" (mobj state) as well as the player's inputs and so on. I was able to do this fairly quickly thanks to the Managed Doom source port (by @Sinshu), made in C# (which is the language I know best and most convenient to do this easily). The CSV format isn't optimized, of course, and besides, my format is a mess and almost unusable. That wasn't the point, but it was the quickest way to see how it looks The CSV output looks like this (~60MB (!!!) for one demo, it takes 16 seconds): the format : gametick,datatype, and other values (for things: mobj type, posX/Y/Z, target, health, frame). Mobj type MiscXX are items (health/armor bonus...) For linedefs and sectors, I can also extract the sector number, action number, direction (front and back sectors) and tags. I haven't gone any further than what's been done so far, I'm a developer, not an AI engineer. I just wanted to verify and demonstrate that it's theoretically possible to train an AI with demo data as input, pretty quickly I guess, obviously with an optimized method and data format. I'm quite surprised that no one has tried, except VizDoom source port. For the test I used a demo on E1M1 UV-Max by Simon Widlake in 3:36.