Get Started with ML-Agents in Unity - Part 2: Basic Concepts
In this tutorial, we explore how Unity’s ML-Agents framework implements Reinforcement Learning. We break down the 'PushBlock' example, covering key RL concepts such as observations, actions, and rewards.
Ready to build your own ML-Agents project? Stay tuned for Part 3, where we’ll start creating a custom project from scratch!
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▬ Timestamps ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
0:00 - Intro
0:57 - What is RL?
2:10 - ML-Agents Examples Project
2:46 - PushBlock Scene
4:11 - PushAgentBasic Script
5:25 - Initialization
6:00 - Episodes
7:33 - Observations
10:47 - Actions
12:10 - Rewards & Penalties
13:35 - Outro
▬ Useful Links ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
► ML-Agents Github documentation: https://docs.unity3d.com/Packages/com...
► Example Learning Environments: https://github.com/Unity-Technologies...
▬ Credits ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
► Music by - CO.AG Music: / @co.agmusic
#unity #ai #mlagents #reinforcementlearning