The main goal of XenTorch module is to save time making neural networks in Studio, simplify the process, thus expanding the opportunity for more neural network projects on Roblox. This module is capable of creating and training fully connected architectures.
Current Capabilities
Note: Check marks indicate completed features, crosses indicate features which are being worked on.
Build network according to given parameters (layer info and functions)
Linear Layers
Convolutional Layers
Biases
Activation Functions
Back Propagation: Normal/Stochastic Gradient Descent
Genetic Algorithm :
Recurrent Algorithm
Save/Load Network
Current Activation and Cost Functions:
ReLU
ReLU Derivative
Sigmoid
Sigmoid Derivative
Softmax
Softmax Derivative (Partial Support)
Mean Squared Error
Mean Squared Error Derivative
Good question! The main reason why you would choose this module over the other, is that it’s more intuitive. If you compare the example code of Kironte’s module to this, you can notice the difference
in complexity immediately. As I said in the post, the goal of this module is to help you build architectures easily. If you have any more concerns, please let me know.
Can we classify this post as community resource already? There is currently no resource we can use, it merely seems like a press release for now.
It looks really promising though! I would definitely consider using your module, as I’m working on a lot of AI-based projects lately (such as self-driving pursuit cars) I would love it if you could provide real use-case examples when you release!
Release Date: Initial version will be released this week.
Current Bugs & Errors
Roblox rounds some of the multiplications to 0, so only very small learning rates can be used with big networks.
Priority Features To Be Added
Full Softmax Derivative
Training/Test Data Separator
Cost Indicator Function
Saving/Loading Networks
API Manual
Personal Thoughts
The amount of hours I put into debugging the gradient algorithm was pain staking, but I finally got it to work properly. As an example project, after the initial release I’m planning on making an NPC AI which mimics how ordinary players walk to points and get around obstacles. This is my first public module and I hope everything goes well!
Of course! You can create classifiers, vehicle automation and much more. The benefit of using neural networks is that it takes away the need to manually code everything, and even turns out to be better than a manually programmed AI most of the time if utilised correctly.
What if I’m considering making something that makes a UI with a UDim2 value move to a goal UDim2 value, but naturally? Does that sound like something neural network-worthy? That’s the only project I have right now that could probably use this.
For something like that, I would create a function which outputs a position, given an input of time. And a neural network is essentially a multi-dimensional function which adapts to training inputs. So in my opinion, it’s something that a neural network can achieve, the only down side which I can think of is that you would need to create your own transitions manually first and record the data.
This seems really interesting and I would love to use this, but I don’t understand how Nueral networks and machine learning works. Any sort of beginners guide so I can work my way up to this Module?
