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 …

The tension between deduction and induction is perhaps the most fundamental issue in
areas such as philosophy, cognition and artificial intelligence (AI). The deduction camp …

We present two novel algorithms for learning formulas in Linear Temporal Logic (LTL) from
examples. The first learning algorithm reduces the learning task to a series of satisfiability …

We introduce the query-by-example (QBE) paradigm for query answering in the presence of
ontologies. Intuitively, QBE permits non-expert users to explore the data by providing …

General game playing (GGP) is a framework for evaluating an agent's general intelligence
across a wide range of tasks. In the GGP competition, an agent is given the rules of a game …

The tension between deduction and induction is perhaps the most fundamental issue in
areas such as philosophy, cognition and artificial intelligence. In this chapter, we survey …

In the logical framework introduced by Grohe and Tur\'an (TOCS 2004) for Boolean
classification problems, the instances to classify are tuples from a logical structure, and …

In the design of analytical procedures and machine learning solutions, a critical and time-
consuming task is that of feature engineering, for which various recipes and tooling …

We consider weighted structures, which extend ordinary relational structures by assigning
weights, ie elements from a particular group or ring, to tuples present in the structure. We …

Probabilistic team semantics is a framework for logical analysis of probabilistic
dependencies. Our focus is on the axiomatizability, complexity, and expressivity of …