still only at ~30 replay folders. if anyone has time to send some over i would greatly appreciate it!

new BBScript version, this adds support for the latest Guilty Gear Strive update. it also stabilizes some changes kkots made, which fix formatting for scripts where ArcSys devs didn't close scopes correctly, as well as adding much more Xrd info
github.com/super-contin...

if anyone has more Xrd replay data folders they're able to send over, i would appreciate it, going to try and continue work on the data science stuff i'm doing, but i want to get the most representative sample of Xrd play that i can

something went very wrong this time

this doesnt seem to apply to directions though, it can charge for flashkick as leo perfectly fine

the model seems to have trouble holding buttons down, i think it might be from the temperature sampling but i don't know if i can fix that

new model, this time it's trained to predict further ahead in the future, hoping that if i tweak this right it will learn to plan ahead better and maybe execute real combos, there's already some improvement to sols short strings but it doesn't seem to be enough yet

early version of a new model, seems to be a bit better at short combo strings but still cant do much more than that, also still has some pretty silly decision making in neutral. its starting to feel less like a bot and more like a very weird human player which is cool though

alright, now that the button issue is fixed, here's a newer model, both players are bots. it's currently quite random but i'm trying to improve that

alright, now that the button issue is fixed, here's a newer model, both players are bots. it's currently quite random but i'm trying to improve that

this is a silly problem to have missed but now that i've fixed it i can start improving the model again

after trying to debug the 5D spam assuming it was an issue with the model itself, i've realized it's because i forgot to change the Xrd controller binds back to the default after playing a bit, meaning the program automating the inputs was pressing the incorrect buttons the whole time

been working on player input prediction using the replay dataset. both players here are bots. still a rough result, but i've made a lot of progress since starting

see my recent posts for dataset-related stuff, i recently got a few more replay folders that i'll be adding soon
bsky.app/profile/topt...

at the moment i've got a lot of other projects that i'm working on, i think it would be possible to implement something that gathers data about games that are being played live, but it would need infrastructure i currently dont have. i am currently working on gathering a replay dataset though

The total number of times a character appears in the current Xrd dataset: Faust: 793 Ky: 642 Raven: 569 Sol: 448 Slayer: 388 Dizzy: 351 Sin: 294 Baiken: 257 Haehyun: 230 Elphelt: 209 Millia: 194 Bedman: 113 Leo: 109 Ino: 106 Chipp: 96 Johnny: 82 May: 68 Answer: 54 Venom: 45 Potemkin: 44 JackO: 35 Jam: 33 Axl: 27 Ramlethal: 19

if you would like to help build this dataset, i would greatly appreciate anyone sending me more replay folders, especially the ones for any character with <100 appearances! just compress the "REPLAY" folder inside the "SAVE" folder in your Xrd install and send it over

i've been trying to work out how i might give a better intuition for the distance values, cS activation range is a good idea. i might go with that and then a marker for something like "half screen away". need to take some measurements

The total number of times a character appears in the current Xrd dataset: Faust: 793 Ky: 642 Raven: 569 Sol: 448 Slayer: 388 Dizzy: 351 Sin: 294 Baiken: 257 Haehyun: 230 Elphelt: 209 Millia: 194 Bedman: 113 Leo: 109 Ino: 106 Chipp: 96 Johnny: 82 May: 68 Answer: 54 Venom: 45 Potemkin: 44 JackO: 35 Jam: 33 Axl: 27 Ramlethal: 19

if you would like to help build this dataset, i would greatly appreciate anyone sending me more replay folders, especially the ones for any character with <100 appearances! just compress the "REPLAY" folder inside the "SAVE" folder in your Xrd install and send it over

characters which are not displayed have <50 examples

this finds grounded normals that are not in a combo, happen midscreen (where midscreen means "both characters within the middle 80% of the screen), and not in the first ~100 frames of a match (removes roundstart bias). range is defined as "the distance between players on frame 1 of the attack"

A chart of the distance between characters during each successful midscreen grounded normal attack. Represented as a density plot

been working on more ways to visualize the xrd replay dataset. here is a density plot illustrating the distance between the character and the opponent when the character uses a grounded normal attack

once i get more data it will probably end up with whoever's last overlapping everything, so maybe eventually i'll need to move to random z-ordering, but for now it seems to work alright

now that i think about it, sorting by representation would probably be a good idea, would make the least represented characters most visible

characters are grouped in alphabetical order to batch icon drawing, lowest values being drawn last, so venom and sol take priority. sol is also one of the characters that has lot's of representation in the data

trying to come up with more ways to plot the data i have, here's one match with x/y over time, creates a cool little structure, nothing too surprising here though, i think i should focus on resources and state-related stuff next

had a silly dataviz idea, here is a video displaying the positions of every character in every Xrd replay i've recorded data for so far.

i don't know if anyone would want to use the underlying code here exactly, but i am considering writing some sort of blog post explainer on the general theory behind it once i finish working out more of the engine and maybe adding netcode. i think it would probably have value to document that

Lua code describing a forward walk state for Ryu in a test fighting game engine.

Lua code defining motion input parsing for 236, a button being pressed, and the composition of the two, declaratively constructing a 236A motion input parser

been spending time chipping away at a fighting game framework. currently have motion inputs and states worked out, they are very flexible and take after the concepts i've learned modding arcsys games. no test footage worth sharing yet, but i find the example code satisfying

feel free to send more if possible, i want as many examples as i can get, 2300 rounds is good, but ideally i want a replay folder of good examples for all characters

of course! i don't have a limit to how much data i want right now, anything helps