In the first part I analyzed the folder structure of a Unity game. The next step is to access the data of the game.
In this blog, I will go over common tools for hacking Unity games.
Autor: Martin Haring
Reinforcement Learning – Topic Overview
This blog is a dedicated summary of this topic’s journey.
Reinforcement Learning – Hacking Unity Games, Part 1
The next step in this project is to hack into the roll-a-ball game and extract some important information (e.g. camera display, score). The AI will use that information to learn to play in later stages.
In this blog, I go over the internal structure of Unity games.
Reinforcement Learning – The Roll-a-Ball Game
In this blog, I introduce the „Roll-a-Ball“ game: a small game I specifically developed for this topic.
Reinforcement Learning – The next step
This blog is the metaphorical bridge between Metroid Learning and the next project, which brings the concept of learning by trial and error into the Unity game engine.
Metroid Learning – Conclusions
In this blog, I briefly summarize this project, present the final test results and finish with both objective conclusions and subjective lessons learned.
Metroid Learning – Trough of Disillusionment
In this blog, I briefly philosophize about the current state of the project.
Metroid Learning – The Anti-Controller
While the AI learns to play, I want to do a small side project. The idea is quite simple: I aim to prototype an ‚unusable‘ controller – and let other people play with it. This is relevant to this topic because it showcases the trial-and-error theme quite well. Like the AI, players need to figure out the controls first to advance in the game.
In this blog, I will create a prototype of an ‚Anti-Controller‘.
Metroid Learning – DEV – Final touch
In this blog, I give an overview about the latest project changes; one last time.
Metroid Learning – DEV – Quality of Life changes
In this blog, a list of the latest project related changes is given.