Reinforcement Learning – Exploring the Unity ML-Agents Toolkit

Last week I discovered and introduced the ML-Agents toolkit, which is a Unity utility that applies Machine Learning to Unity applications. A first look on the kart racing example project provided insights into this specific field. In summary, an RL agent receives some form of input and improves its behavior based on that input over time until its performance reaches a desired degree of quality. On the one hand, this utility fulfills my initial goal to test applications using AI while on the other hand, it even surpasses my intentions by providing extra features, like training NPCs.

In this blog, example projects of the ML-Agents toolkit are briefly shown and summarized.

Reinforcement Learning – Lost Chapters – RL in AI

Researching on the topic lead to the conclusion that I skipped one of the most important steps – assigning Reinforcement Learning (RL) bots their place in the field of Artificial Intelligence (AI). There is a lot of ground to cover, so it is now time to catch up on it.

In this blog, I properly introduce RL’s place in the field AI.