Robert Lange

Robert Lange on learning vs hard-coding, meta-RL, Lottery Tickets and Minimal Task Representations, Action Grammars and more!

Show Notes

Robert Tjarko Lange is a PhD student working at the Technical University Berlin.

Featured References

Learning not to learn: Nature versus nurture in silico
Lange, R. T., & Sprekeler, H. (2020)

On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
Vischer, M. A., Lange, R. T., & Sprekeler, H. (2021).

Semantic RL with Action Grammars: Data-Efficient Learning of Hierarchical Task Abstractions
Lange, R. T., & Faisal, A. (2019).

MLE-Infrastructure on Github


Additional References

• RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning, Duan et al 2016
• Learning to reinforcement learn, Wang et al 2016
• Decision Transformer: Reinforcement Learning via Sequence Modeling, Chen et al 2021

Creators & Guests

Host

Robin Ranjit Singh Chauhan

🌱 Head of Eng @AgFunder 🧠 AI:Reinforcement Learning/ML/DL/NLP🎙️Host @TalkRLPodcast 💳 ex-@Microsoft ecomm PgmMgr 🤖 @UWaterloo CompEng 🇨🇦 🇮🇳

What is TalkRL: The Reinforcement Learning Podcast?

TalkRL podcast is All Reinforcement Learning, All the Time.
In-depth interviews with brilliant people at the forefront of RL research and practice.
Guests from places like MILA, OpenAI, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute.
Hosted by Robin Ranjit Singh Chauhan.