Learning RL Algorithms via ML

"In-context Reinforcement Learning with Algorithm Distillation" is a new paper from DeepMind about learning how to learn how to do Reinforcement Learning (RL) using behavior cloning over a learning history with a Transformer. The idea is simple, but I think the implications could be big for the future.

Outline
0:00 - Intro
0:30 - Why I like this paper
2:08 - MLClear
3:17 - Algorithm Overview
7:50 - Bandits
9:06 - Robustness Results
15:08 - Speedup Results
22:00 - Other …

algorithms