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

Authors

  • Gunjan Singh Indraprastha Institute of Information Technology, IIIT, Delhi, India
  • Sutapa Mondal Indraprastha Institute of Information Technology, IIIT, Delhi, India
  • Sumit Bhatia IBM Research AI, New Delhi, India
  • Raghava Mutharaju Indraprastha Institute of Information Technology, IIIT, Delhi, India

Keywords:

Neuro-symbolic Reasoning, OWL 2 Reasoner, Description Logic Reasoner

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.

Downloads

Published

2021-05-18

How to Cite

Singh, G., Mondal, S., Bhatia, S., & Mutharaju, R. (2021). Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15891-15892. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17942

Issue

Section

AAAI Student Abstract and Poster Program