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Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning.
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Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent ought to take ...
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Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the ...
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Deep learning is the subset of machine learning methods based on neural networks with representation learning. The adjective "deep" refers to the use of ...
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In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent to human preferences.
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Jan 28, 2022 · Abstract:Fine-tuning reinforcement learning (RL) models has been challenging because of a lack of large scale off-the-shelf datasets as well ...
Q learning is a model free reinforcement learning algorithm. It is named after the “quality function” at the heart of the method (and has nothing to do with the ...
In reinforcement learning, the entity that uses a policy to maximize the expected return gained from transitioning between states of the environment.
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