Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract)

Gunjan Singh, Sutapa Mondal, Sumit Bhatia, Raghava Mutharaju

AAAI 2021 pp. 15891-15892

doi:10.1609/AAAI.V35I18.17942 /aaai/2021/singh2021aaai-neuro/

Abstract

With the goal to find scalable reasoning approaches, neuro-symbolic techniques have gained significant attention. However, the existing approaches do not take into account the inference capabilities of ontology languages that are based on expressive description logic (such as OWL 2). To fill this gap, we propose two approaches: an ontology-based embedding model for theories in EL++ description logic and a reinforcement learning-based solution for efficient tableau-based reasoning on description logic. We describe promising initial results of our efforts towards these directions and lay down the direction for future work.

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Cite

Text

Singh et al. "Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I18.17942

Markdown

[Singh et al. "Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/singh2021aaai-neuro/) doi:10.1609/AAAI.V35I18.17942

BibTeX

@inproceedings{singh2021aaai-neuro,
  title     = {{Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract)}},
  author    = {Singh, Gunjan and Mondal, Sutapa and Bhatia, Sumit and Mutharaju, Raghava},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {15891-15892},
  doi       = {10.1609/AAAI.V35I18.17942},
  url       = {https://mlanthology.org/aaai/2021/singh2021aaai-neuro/}
}