Agent Learns to do Reinforcement Learning

"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 - ClearML 3:17 - Algorithm Overview 7:50 - Bandits 9:06 - Robustness Results 15:08 - Speedup Results 22:00 - Other Results 23:00 - Conclusion ClearML - https://bit.ly/3GtCsj5  Social Media YouTube -    / edanmeyer   Twitter -   / ejmejm1   RL AD Paper - https://arxiv.org/abs/2210.14215