Pangaea

i've received bug reports of the Angel overlay not appearing, or the game crashing upon startup with Angel installed. these issues were due to MSI Afterburner conflicting with the overlay, and Windows 11 Smart App Control. unfortunately it seems like i can't fix the issues directly

new version of Angel is out, i fixed lots of the bugs that were reported in the first version. accessing online play should be quicker and more reliable for everyone, especially people with long-distance connections. there's a few new features too! github.com/super-contin...

finally releasing a project i've spent a lot of time working on. a mod for Arcana Heart 3 XTEND which adds several improvements, including rollback! special thanks to @armonte.meltyblood.org for doing much of the reversing work download and install guide here: github.com/super-contin...

created a hitbox viewer mod for Arcana Heart

Xrd model now uses RL, this isn't a finished training run, and no online RL has been applied yet as i'm still working on the mod setup for that, but i'm very happy with the progress! here's the model playing against itself, i think it's a massive step up from the last footage i posted

for those who dont know what "RL" means: its reinforcement learning. the models i was showing before were trained to mimic player behavior as accurately as possible, this one has a second phase of training which tells it to estimate which decisions were "good" and focus on those actions

working on figuring out the meter gain values for each character, i've created a table of each characters values, most of them are fairly obvious, just meter added and scaled by tension pulse somehow, but i can't figure out what "Guard Balance Tension" is supposed to be. any ideas?

switched to training on whole rounds instead of small context windows, i'm pretty shocked by how big the improvement is compared to what i had before. this also enables performance optimizations which make it way easier to run larger models in realtime. here's a Johnny vs Faust round as an example

trying to figure out how to measure the average APM of each character in the Xrd dataset. here i'm searching for changes in the player state that coincide with a button press. honestly not sure what's going on with zato

in this case i actually expected zato to be unusually low, as eddies attacks wouldn't be counted because theyre a separate entity changing state, not zato. there must be some other thing boosting him unusually high, that's what happens when you have few samples of some characters

trying to figure out how to measure the average APM of each character in the Xrd dataset. here i'm searching for changes in the player state that coincide with a button press. honestly not sure what's going on with zato

the input prediction model takes the state that characters are in as input. these are placed in a vector space, starting out in random positions, but are slowly positioned so that states that are "related" end up closer together. here's a visualization of the random placement vs the sorted result

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

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 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

characters which are not displayed have <50 examples

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

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

i'm now up to 10 replay folders total, assuming all are full (Xrd has a 100 replay limit) and use best 2 of 3, that gets me around 2300 rounds of data! i'm always open to more, but this seems like a good start for some testing. thank you to all who submitted their folders!