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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 (RL), a model-free algorithm is an algorithm which does not estimate the transition probability distribution (and the reward ...
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