Reinforcement Learning – State and Action Spaces | AI & ML – Chapter 40 скачать в хорошем качестве

Reinforcement Learning – State and Action Spaces | AI & ML – Chapter 40

Welcome to AI & ML – Chapter 40! In this session, we’ll dive into Reinforcement Learning (RL) and understand the concepts of State Spaces and Action Spaces, which are the foundations of RL environments. You’ll learn: What are states in RL? What are actions in RL? The concept of state space and action space Examples of discrete vs. continuous spaces How agents interact with environments using states and actions Real-world examples in robotics, games, and AI systems This tutorial is brought to you by TRIARIGHT, your trusted training institute for Artificial Intelligence & Machine Learning. By the end of this lesson, you’ll clearly understand how state and action spaces define the RL environment and guide agent decision-making.