RL
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Explore more → **RL**
What is RL?
Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with an environment to maximize a cumulative reward. The agent isn't explicitly told how to act, but instead discovers which actions yield the most reward through trial and error. RL is commonly used in robotics, game playing (like Go and chess), and autonomous driving.
What other technologies are related to RL?
RL Complementary Technologies
CV
Computer vision can be used as a source of input or a tool for RL agents, enabling them to perceive and interact with visual environments.
NLP
Natural Language Processing can be used to provide textual input or interpret textual output from RL agents, useful for tasks involving communication or understanding instructions.
LLMs
Large language models (LLMs) can be used as components within RL systems, such as for generating actions, providing context, or shaping rewards. They are also sometimes used for reasoning about RL problems.
Number of organizations that mention technology
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Which job functions commonly mention RL?
Applied Scientist
0.2% of all Applied Scientist jobs mention RL
View 18
jobs on Sumble
Research Scientist
0.1% of all Research Scientist jobs mention RL
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jobs on Sumble
AI Engineer
0.1% of all AI Engineer jobs mention RL
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jobs on Sumble
Machine Learning
0.1% of all Machine Learning jobs mention RL
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jobs on Sumble
Data, Analytics & Machine Learning
230 Data, Analytics & Machine Learning jobs mention RL
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jobs on Sumble
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