What Is Reinforcement Learning?
Reinforcement learning is a type of machine learning in which an agent learns by trial and error, taking actions in an environment and receiving rewards or penalties. Over time it learns a strategy that maximizes total reward. It has been used for game-playing systems, robotics, and training AI assistants.
Reinforcement Learning from Human Feedback (RLHF)
In RLHF, people rate or compare model responses, and those preferences are used as a reward signal to make a language model more helpful and appropriate.
Exploration vs. Exploitation
An agent must balance trying new actions to discover better rewards with repeating actions already known to work.
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🔗 Related Terms
More AI & Technology Terms
- AI Bias
- AI Hallucination
- Algorithm
- API (Application Programming Interface)
- Artificial General Intelligence (AGI)
- Artificial Intelligence (AI)
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Last updated: September 29, 2026. This definition is for general educational purposes only. It is not financial, investment, tax, legal, or medical advice, and it does not recommend any product or course of action. For decisions about your own situation, consult a qualified professional.