Latent State Discovery in Reinforcement Learning

Abstract: There are three core orthogonal problems in reinforcement learning: (1) Crediting actions (2) generalizing across rich observations (3) Exploring to discover the information necessary for learning. Good solutions to pairs of these problems are fairly well known at this point, but solutions for all three are just now being discovered. I’ll discuss several such results and dive into details on a few of them.

bioinformaticsgame theoryinformation theorymachine learningneural and evolutionary computingclassical analysis and ODEsoptimization and controlstatistics theory

Audience: researchers in the topic

IAS Seminar Series on Theoretical Machine Learning

Series comments: Description: Seminar series focusing on machine learning. Open to all.

Register in advance at forms.gle/KRz8hexzxa5P4USr7 to receive Zoom link and password. Recordings of past seminars can be found at www.ias.edu/video-tags/seminar-theoretical-machine-learning