13 Reinforcement Learning: Policy Gradients, Q Learning, AlphaGo, AlphaStar (MLVU2019)
Channel: MLVU
Date: 21/03/2019

slides: https://mlvu.github.io/lectures/71.Reinforcement%20Learning.annotated.pdf
course materials: https://mlvu.github.io

Today we discuss the most generic abstract task in machine learning: reinforcement learning. Reinforcement Learning models an agent that interacts with its environment. We dicuss the basic task of RL, and three ways to solve it: random search, policy gradients and Q learning.

Then, we have a look at some recent successes of deep reinforcement learning (combining RL with deep neural networks): AlphaGO, AlphaZero and AlphaStar.