Episode 43: Deep Reinforcement Learning

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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A podcast that explores the unseen and surprising connections between nearly everything, with special emphasis on intelligence and the search for Artificial General Intelligence (AGI) through the lens of Karl Popper's Theory of Knowledge. David Deutsch argued that Quantum Mechanics, Darwinian Evolution, Karl Popper's Theory of Knowledge, and Computational Theory (aka "The Four Strands") represent an early 'theory of everything' be it science, philosophy, computation, religion, politics, or art. So we explore everything. Support us on Patreon: https://www.patreon.com/brucenielson/membership