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| Definition | : | Reinforcement Learning from Human Feedback |
| Category | : | Computing » Artificial Intelligence |
| Country/ Region |
: | Worldwide
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| Popularity | : |
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Initialism
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Reinforcement Learning from Human Feedback (RLHF) is a type of machine learning method where an agent learns to make decisions by receiving feedback from a human in the form of rewards or punishments.
Note:
An agent is a software or algorithm that is designed to take actions in an environment in order to achieve a specific goal or set of goals.
The full form of RLHF is Reinforcement Learning from Human Feedback
Reinforcement Learning from Human Feedback
