In line with the general trend in artificial intelligence research to create intelligent systems
that combine learning and symbolic components, a new sub-area has emerged that focuses …

Knowledge-enhanced neural machine reasoning has garnered significant attention as a
cutting-edge yet challenging research area with numerous practical applications. Over the …

Knowledge engineering is a discipline that focuses on the creation and maintenance of
processes that generate and apply knowledge. Traditionally, knowledge engineering …

Neural-symbolic computing (NeSy), which pursues the integration of the symbolic and
statistical paradigms of cognition, has been an active research area of Artificial Intelligence …

This open access book provides a comprehensive overview of the state of the art in research
and applications of Foundation Models and is intended for readers familiar with basic …

Given the popular presupposition of human reasoning as the standard for learning and
decision making, there have been significant efforts and a growing trend in research to …

Inferring reward functions from demonstrations and pairwise preferences are auspicious
approaches for aligning Reinforcement Learning (RL) agents with human intentions …

In this paper we introduce Detect, Understand, Act (DUA), a neuro-symbolic reinforcement
learning framework. The Detect component is composed of a traditional computer vision …

The area of neurosymbolic artificial intelligence (Neurosymbolic AI) is rapidly developing
and has become a popular research topic, encompassing subfields, such as neurosymbolic …

The imposition of hard constraints on the output of neural networks is a highly desirable
capability, as it instills confidence in AI by ensuring that neural network predictions adhere to …