Q-learning
A traditional reinforcement learning algorithm that the paper shifts away from by using a different objective.
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Videos Mentioning Q-learning
![[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton](https://i.ytimg.com/vi/25FsKN0f8gQ/maxresdefault.jpg)
[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton
Latent Space
A traditional reinforcement learning algorithm that the paper shifts away from by using a different objective.
Michael Littman: Reinforcement Learning and the Future of AI | Lex Fridman Podcast #144
Lex Fridman
An off-policy reinforcement learning algorithm that learns the value of actions in specific states, allowing agents to learn optimal behavior regardless of the policy being followed.
MIT 6.S094: Deep Reinforcement Learning
Lex Fridman
A model-free reinforcement learning algorithm that aims to find the optimal action-selection policy for an agent by learning the value of actions in given states.
MIT 6.S094: Deep Reinforcement Learning for Motion Planning
Lex Fridman
An off-policy reinforcement learning algorithm that learns to approximate an optimal policy by estimating the Q-value (quality) of state-action pairs through experience.