PAI course notes

I took part in the course Probabilistic Artifical Intelligence in the autumn festival 2019, which is opened by the super star🌟Professor Andreas Krause. This serie of notes was created during my review of the course and contained the main ideas/concepts/methods of each lecture, my own thoughts/ideas/questions as well as out-of-class helpful materials. For more detailed information, please refer to the lecture notes posted on the course homepage.

Overview

The focus of this course is about reasoning and decision making under uncertainty.

• Probabilistic reasoning
  • Bayes Net
  • graphical models
• Learning
  • Bayesian deep learning
• Planning under uncertainty
  • MDPs
  • POMDPs
• Deep reinforcement learning

Content

• Foundamention

• Bayesian Network 1 - Basic

• Bayesian Network 2 - Inference

• Reasoning over Time

• Probabilistic Planning

• Learning

• Reinforcement Learning

Others

Below is my cheatsheet for the final exam.