The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)
-
Updated
May 25, 2021 - Python
The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)
Source code of the ICML24 paper "Self-Composing Policies for Scalable Continual Reinforcement Learning" (selected for oral presentation)
The official implementation of Memory-efficient DQN algorithm.
Add a description, image, and links to the continual-reinforcement-learning topic page so that developers can more easily learn about it.
To associate your repository with the continual-reinforcement-learning topic, visit your repo's landing page and select "manage topics."