What is reinforcement learning in AI?
Reinforcement learning is a type of machine learning where an agent learns to make decisions by taking actions in an environment to maximize cumulative rewards.
How does it differ from supervised learning?
In supervised learning, the model learns from labeled data, while in reinforcement learning, the agent learns from the consequences of its actions without explicit labels.
Can you give me an example of reinforcement learning in action?
Sure! A common example is training a robot to navigate a maze. The robot receives rewards for reaching the goal and penalties for hitting walls, learning to optimize its path.
What are some real-world applications of reinforcement learning?
Reinforcement learning is used in various fields, including robotics, game playing (like AlphaGo), autonomous vehicles, and personalized recommendations.
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