Episode 43: Deep Reinforcement Learning episode artwork

EPISODE · Apr 18, 2022 · 1H 21M

Episode 43: Deep Reinforcement Learning

from The Theory of Anything · host Bruce Nielson and Peter Johansen

In this video upload available on Spotify (we'll try this once and see how it's received), we revisit Reinforcement Learning (from way back in episode 28) and this time discuss how to turn it into Deep Reinforcement Learning by swapping out the Q-Table and putting a neural network in its place. The end result is a sort of 'bootstrapping intelligence' where you let the neural net train itself.  We also discuss:  How this, if at all, relates to animal intelligence.  Is RL a general purposes learner?  Is it a path to AGI? Links: Github Code Base Presentation Slide Pack Youtube version

In this video upload available on Spotify (we'll try this once and see how it's received), we revisit Reinforcement Learning (from way back in episode 28) and this time discuss how to turn it into Deep Reinforcement Learning by swapping out the Q-Table and putting a neural network in its place. The end result is a sort of 'bootstrapping intelligence' where you let the neural net train itself.  We also discuss:  How this, if at all, relates to animal intelligence.  Is RL a general purposes learner?  Is it a path to AGI? Links: Github Code Base Presentation Slide Pack Youtube version

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Episode 43: Deep Reinforcement Learning

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This episode was published on April 18, 2022.

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In this video upload available on Spotify (we'll try this once and see how it's received), we revisit Reinforcement Learning (from way back in episode 28) and this time discuss how to turn it into Deep Reinforcement Learning by swapping out the...

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