The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)
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Updated
May 25, 2021 - Python
The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)
Accelerating Research in Plasticity-Motivated Deep Reinforcement Learning.
Source code of the ICML24 paper "Self-Composing Policies for Scalable Continual Reinforcement Learning" (selected for oral presentation)
Agar.io for Continual Reinforcement Learning
The official implementation of Memory-efficient DQN algorithm.
implementation of "Knowledge Retention in Continual Model-Based Reinforcement Learning"
A benchmark for Continual Multi-Agent Reinforcement Learning on the Overcooked environment.
CleanRL implementation of "Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn"
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