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Grounded QA
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Summary: Documentation and files about the Grounded QA component, as part of the GUT-AI Initiative <https://github.com/GUT-AI/gut-ai>_.
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About
The purpose of this component is to perform Grounded Question Answering (Grounded QA) by applying Grounded Cognition on QA tasks on multiple mobile robots or multiple aerial robots (drones) or a combination of them using Multimodal Learning (i.e. visuo-linguistic abilities)
Main papers
Selected publications
^^^^^^^^^^^^^^^^^^^^^
- 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
References
^^^^^^^^^^
See References <references/README.rst>_.
Component files
Component page
^^^^^^^^^^^^^^
Thanks to OSF (by the Center for Open Science <https://www.cos.io/>_), the project is temporarily hosted at:
Component DOI
^^^^^^^^^^^^^
Project identifier: https://doi.org/10.17605/OSF.IO/8FRXM
Component dependencies
^^^^^^^^^^^^^^^^^^^^^^
This component depends on the following components of GUT-AI:
QA <https://github.com/GUT-AI/gut-ai/blob/master/components/README.rst#component-c4-9-qa>_VSPT <https://github.com/GUT-AI/gut-ai/blob/master/components/README.rst#component-c4-10-vspt>_Multi-Agent Communication <https://github.com/GUT-AI/gut-ai/blob/master/components/README.rst#component-c4-11-multi-agent-communication>_Multi-Robot Path Planning <https://github.com/GUT-AI/gut-ai/blob/master/components/README.rst#component-c4-12-multi-robot-path-planning>_
Environment simulators
^^^^^^^^^^^^^^^^^^^^^^
See Simulators <https://github.com/GUT-AI/gut-ai/blob/master/simulators/README.rst>_.
Datasets
^^^^^^^^
See Datasets <https://github.com/GUT-AI/gut-ai/blob/master/README.rst>_.
Model Zoos
^^^^^^^^^^
See Model Zoos <https://github.com/GUT-AI/gut-ai/blob/master/model_zoos/README.rst>_.
Getting involved
Community Discord <https://github.com/GUT-AI/gut-ai/>_ for collaboration and discussion.
How to cite this
If you want to do so, feel free to cite <CITATION.cff>_ this component in your publications:
::
@article{kourouklides2022gqa,
author = {Ioannis Kourouklides},
journal = {OSF Preprints},
title = {Grounded QA},
year = {2022},
doi = {10.17605/osf.io/8frxm},
license = {Creative Commons Zero CC0 1.0}
}
License
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Creative Commons Zero CC0 1.0 (Public Domain) <LICENSE>_