Neuro-symbolic AI is an effective method for improving the overall performance of AI models
by combining the advantages of neural networks and symbolic learning. However, there are …

Symbolic framework is one of the learning frameworks based on symbol system and its
symbolic logic. We first overview symbolism, symbolic learning theory, physical symbol …

This thesis addresses the challenge of evaluating candidate logical formulas, with a specific
focus on axioms, by synergistically combining machine learning with symbolic reasoning …

Cette thèse aborde le défi de l'évaluation des formules logiques candidates, avec un accent
particulier sur les axiomes, en combinant de manière synergique l'apprentissage …

In the field of neurosymbolic computing, there is a lack of standardized benchmark datasets
specifically designed for evaluating neurosymbolic ontology reasoning systems. Currently …

Recently, there has been significant progress in the development of robust and highly
scalable neuro-symbolic description logic reasoners. However, the field faces challenges …

Neuro-Symbolic approaches bring together symbolic logic and neural network-based
machine learning. This has the potential to build robust reasoning systems. However, the …