
A latent state can enable vastly better planning, exploration, and credit assignment by keeping task-relevant information while discarding distractions and irrelevant details. For example, in video games, there is a game-engine state which has all relevant information for the underlying dynamics. This tutorial will discuss how we can discover such a latent state in the real world directly from observations, and the kinds of latent states which are known to be discoverable. The tutorial discusses theoretical developments at a high-level, to explain the key pieces of understanding as well as their limitations. The tutorial will discuss where the state-of-the-art is experimentally, and what is currently ready for usage in real-world applications.

Senior researcher @ Microsoft Research