Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two
hitherto distinct approaches.” Neuro” refers to the artificial neural networks prominent in …

This survey explores the integration of learning and reasoning in two different fields of
artificial intelligence: neurosymbolic and statistical relational artificial intelligence …

We introduce DeepProbLog, a probabilistic logic programming language that incorporates
deep learning by means of neural predicates. We show how existing inference and learning …

Although deep reinforcement learning has become a promising machine learning approach
for sequential decision-making problems, it is still not mature enough for high-stake domains …

Neuro-symbolic and statistical relational artificial intelligence both integrate frameworks for
learning with logical reasoning. This survey identifies several parallels across seven …

Abstract Neuro-Symbolic (NeSy) predictive models hold the promise of improved
compliance with given constraints, systematic generalization, and interpretability, as they …

Perception and reasoning are two representative abilities of intelligence that are integrated
seamlessly during human problem-solving processes. In the area of artificial intelligence …

We study the problem of combining neural networks with symbolic reasoning. Recently
introduced frameworks for Probabilistic Neurosymbolic Learning (PNL), such as …

In today's article, we are going to address the topic of Python (programming language), an
issue that has generated great interest in today's society. Python (programming language) is …

We introduce DeepProbLog, a neural probabilistic logic programming language that
incorporates deep learning by means of neural predicates. We show how existing inference …