Reinforcement Learning at AMMI

This repo includes lecture slides, notebooks and other material for the RL week at AMMI, the African Masters of Machine Intelligence

Policy/Value Iteration

• Day 1 Slides
• Policy/Value Iteration exercises
• Policy/Value Iteration solutions

Extra:

• Supplementary: Policy/Value Iteration in Matrix form
• RL book Chapter 4, Dynamic Programming
• Dynamic Programming lecture video

Monte Carlo and TD learning

• Day 3 Slides
• Monte Carlo / TD exercises
• Monte Carlo / TD solutions

Function Approximation

• Day 5 Slides

Policy Gradient - REINFORCE

• Day 6 Slides
• REINFORCE exercise
• REINFORCE solution
• REINFORCE with learned Baseline exercise
• REINFORCE with learned Baseline solution
• Actor-Critic
• Actor-Critic solution

Extra:

• Policy Gradient Algorithms
• Policy Gradient Explained - Blog Post
• Policy Gradient lecture video

Models and Hierarchy

• Day 8 Slides

Python and Numpy

• Python Basics

Extra:

• Python crash course
• Numpy crash course
• How to build your own Neural Network from scratch in Python

External Resources

• Reinforcement Learning: An Introduction, by Sutton and Barto, 2018. This is the canonical RL book which has everything you need to learn RL.
• RL Course Lectures by David Silver, videos, slides