Summary: Documentation and files about the Continual Learning component, as part of the GUT-AI Initiative.
Table of Contents
The purpose of this component is to perform Continual Learning.
- Kourouklides, I. (2022). Bayesian Deep Multi-Agent Multimodal Reinforcement Learning for Embedded Systems in Games, Natural Language Processing and Robotics. OSF Preprints. https://doi.org/10.31219/osf.io/sjrkh
See References.
Thanks to OSF (by the Center for Open Science), the project is temporarily hosted at:
Project identifier: https://doi.org/10.17605/OSF.IO/TEBPN
This component depends on the following components of GUT-AI:
- (none)
See Simulators.
See Datasets.
See Model Zoo.
- Community Discord for collaboration and discussion.
If you want to do so, feel free to cite this component in your publications:
@article{kourouklides2022cl, author = {Ioannis Kourouklides}, journal = {OSF Preprints}, title = {Continual Learning}, year = {2022}, doi = {10.17605/osf.io/tebpn}, license = {Creative Commons Zero CC0 1.0} }