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Reinforcement Learning Explained: Agents, Actions, Rewards & Real-World Applications
11 months ago
1
Entertainment
Do It Yourself
Reinforcement Learning
Artificial Intelligence
Q-learning
Policy gradients
Machine learning
Agents and rewards
Robotics AI
Self-driving cars AI
DeepMind AlphaGo
In this video, we dive into the fascinating world of Reinforcement Learning (RL) – a key area in Artificial Intelligence (AI). We'll explain the core concepts like agents, actions, and rewards, and how these elements come together to help machines learn from their environments. Explore popular RL algorithms like Q-learning and policy gradients, and see how they're applied in real-world scenarios such as gaming, robotics, and self-driving cars. By the end, you'll have a solid understanding of how RL is transforming industries. Don't forget to like, comment, and subscribe for more AI and tech content!
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