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→Adding Isaac related details to Reinforcement Learning (RL)
Reinforcement Learning (RL) is a machine learning approach where an agent learns to perform tasks by interacting with an environment. It involves the agent receiving rewards or penalties based on its actions and using this feedback to improve its performance over time. RL is particularly useful in robotics for training robots to perform complex tasks autonomously. Here's how RL is applied in robotics, using simulation environments like Isaac Sim and MuJoCo:
== RL in Robotics ==
=== Practical Applications of RL ===
==== Task Automation ====
* Robots can be trained to perform repetitive or dangerous tasks autonomously, such as assembly line work, welding, or hazardous material handling.
* RL enables robots to adapt to new tasks without extensive reprogramming, making them versatile for various industrial applications.
== Training algorithms ==
