Credit to @Cffex for providing the codes for AIs’ movement and sensing.
The full file for the source code in this video can be found here.
(DataPredict’s and MatrixL’s libraries terms and conditions apply due to source code containing these libraries.)
Please send bug reports here. It seems like the library got too large for me to maintain and bug hunting myself.
Hi guys! I introduce you to a new Machine + Deep Learning Library!
Thanks to the object-orientated programming, this version of the library now contains optimizers and many more. More details in the documentation.
Documentation And Tutorials: Welcome to Aqwam’s DataPredict Library! | DataPredict
Pretrained Neural Networks: GitHub - AqwamCreates/DataPredict-Pretrained-Neural-Networks
Source code for a simple usage of reinforcement learning neural network can be found here.
ModuleScript (Release Versions) For This Library:
Release Version 1.6 (Fully Tested Beta 1.19.0) - REINFORCE, Dueling Q Learning And Evolving Neural Network Layer Size!
Release Version 1.5 (Fully Tested Beta 1.18.0) - ActorCritic, A2C, A3C, And Distributed Learning!
Release Version 1.4 (Fully Tested Beta 1.17.0) - More Experience Replays and Reinforcement learning neural networks!
Release Version 1.3 (Fully Tested Beta 1.16.0) - Double Q-Learning Neural Networks.
Release Version 1.2 (Fully Tested Beta 1.15.0) - Q-learning neural networks with experience replay, model parameters merger, OneVsAll and more!
Package For This Library (Recommend For Up-To-Date Library):
ModuleScript (Unstable) For This Library: https://create.roblox.com/marketplace/asset/12591886004/Aqwams-Roblox-Machine-And-Deep-Learning-Library
ModuleScript for Matrix Library: Aqwam's Matrix Library - Roblox
What is machine learning?
Machine learning is a way for computers to predict information based on the data we given to them. Machine learning can do three main tasks: Regression, Classification and Clustering.
Regression: Generates a continuous value (e.g. -1.1, 2.09, 20) from given data.
Classification: Generates a discrete value (e.g. 1, 2, 3), mainly for classifying given data.
Clustering: Generates centroids (center of data) based on the given data and predict which centroids that a data belongs to.
What is deep learning?
It is a more advanced version of machine learning, but mainly covers the neural network models. The training techniques are significantly improved and models are more complex compared to machine learning.
So how do we use this library?
In machine/deep learning, we mainly need to do training before we can predict things. To train, we need a lot of data and choose the correct models so that we can achieve very good results. Once training is done, you can use the model to predict values based on the data that was never seen before by the model.
Retrainable models - for future model improvements
Organized functions - for better control
Optimizers - for increasing training speeds
More complex models - for wider use cases
- Movement prediction
- Make prediction on how long will a player reach certain level
- Spawn an enemy where the difficulty is based on input
- Make an enemy that makes decision between 2 choices (e.g. fighting and running)
- Detect hacking players
- Group players in terms of experience level
- Detect hacking players
What I Have Used It For
In one of my games (zero players, but somewhat released), it is mainly used for:
- Some of my AI Assistants (to help enhance gaming experience and variety)
- Sales analysis for better product pricing strategy (when the game becomes popular).
- AI players for player retention during durations of low players count.
If you are curious how my game looks like, you can have a look here:
[BETA] Terrae Uprising: Pre-Mana - Roblox
Want Better Performance?
The current version uses “MatrixL”, but there is more performant version named “MatrixL-Turbo”, where it has 3x better performance on (some) larger models such as Neural Networks.
You can directly contact me to purchase a license to use the “MatrixL-Turbo” per month. You are expected to give in personal information and perform video calls to ensure that the process is done with our interest.
Who Uses This Library?
- Senior game developers
- University students
- AI enthusiasts
(Some proof can be seen from the likes by other people on this first post.)
Not accepting feature requests. Only bug reports.
Expect this release version 1.6 as the “final” version.
There are two versions: Release (or Stable) and Beta (or Unstable). Choose the first version if you wish to use fully tested version of this library as well as in commercial scale. The latter contains up-to-date version of this library, which may contain bugs.
Don’t forget to leave a like if you find this resource useful!