The Theory of Anything Episode 43: Deep Reinforcement Learning
Apr 18, 2022
The podcast discusses deep reinforcement learning, its relationship to regular reinforcement learning, and its potential application to animal intelligence and AGI. They give examples using code, explore Elon Musk's dedication to solving humanity's problems, and discuss OpenAI's approach to AI research and AGI safety. The podcast also covers Markov decision processes and the challenges of using a Q table in stochastic environments.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7
Introduction
00:00 • 1min
Deep Reinforcement Learning and Examples with Code
01:29 • 4min
Elon Musk's Mission to Save Humanity
05:56 • 4min
OpenAI's Approach to AI Research and AGI Safety
10:18 • 4min
Deep Reinforcement Learning and Markov Decision Processes
14:35 • 26min
Stochastic Environments and Markov Decision Process
40:55 • 31min
Animal Intelligence and Deep Reinforcement Learning
01:12:14 • 9min