Inductive Logic Programming (ILP) is concerned with the task of generalising sets of positive
and negative examples with respect to background knowledge expressed as logic …

Event recognition systems rely on knowledge bases of event definitions to infer occurrences
of events in time. Using a logical framework for representing and reasoning about events …

Modern cosmology and plasma physics codes are now capable of simulating trillions of
particles on petascale systems. Each timestep output from such simulations is on the order …

The pervasive use of AI today caused an urgent need for human-compliant AI approaches
and solutions that can explain their behavior and decisions in human-understandable terms …

We present a novel approach to non-monotonic ILP and its implementation called TAL (Top-
directed Abductive Learning). TAL overcomes some of the completeness problems of ILP …

Systems for symbolic event recognition infer occurrences of events in time using a set of
event definitions in the form of first-order rules. The Event Calculus is a temporal logic that …

To prevent problems and capitalise on opportunities before they even occur, the research
project SPEEDD proposed a methodology, and developed a prototype for proactive event …

Recently there are great efforts on leveraging machine learning and logical reasoning. Many
approaches start from a given knowledge base, and then try to utilize the knowledge to help …

One of the aims of the EU project COLLATE is to design and implement a Web-based
collaboratory for archives, scientists and end-users working with digitized cultural material …

Smart home environments should proactively support users in their activities, anticipating
their needs according to their preferences. Understanding what the user is doing in the …