💻 Unity 2024 ML-Agents | Live AI Robot Training | Kyle 2a0a | PyTorch | Part 8
In this video, I will show you how to train a robotic walker to cooperate with other walkers in a hostile environment using Unity Machine Learning Agents Toolkit.
**Coding** up the `MotionPerceptionSystem` which will be used by Kyle, the robot, to figure out which direction and how fast they should be moving. This is a separate agent and will be trained in a separate scene. It communicates to our current kyle model by updating the target speed and target location to one set by this new motion perception agent. This agent will also take in many more Ray perception sensors for each eye ball. This agent will also have a list of tags which it will learn the ones it likes and dislikes by sharing each agents reward signal with each other.
ML-Agents is an open source project that allows you to create and train intelligent agents using reinforcement learning and deep neural networks. In the previous episodes, we added different features to our robotic walker, such as a negative reward for colliding with another walker, a hostile walker that can attack them, and a reward function that encourages cooperation and survival.
In this episode, we will add a new twist to our robotic walker game: we will remove the stabilizers that keep the ragdoll upright. This means that the ragdoll will fall on the ground and have to learn how to get up by itself. We will see how this affects the training process and the performance of our robotic walker. We will also compare the results with the same walkers that still have the stabilizers.
By the end of this video, you will have a deeper understanding of how to use ML-Agents to create and train agents with complex and realistic physics. You will also have a more challenging and fun robotic walker game with more emergent and diverse behaviors.
This is the seventh video in my Unity Machine Learning series, where I teach you how to use ML-Agents for various games and simulations. If you want to learn more about ML-Agents, check out my other videos and playlists on this topic.
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