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