Abstract Systems for symbolic complex event recognition detect occurrences of events in
time using a set of event definitions in the form of logical rules. The Event Calculus is a …

Logic-based event recognition systems 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 …

Symbolic event recognition systems detect event occurrences using first-order logic rules.
Although existing online structure learning approaches ease the discovery of such rules in …

Handling relational data streams has become a crucial task, given the availability of
pervasive sensors and Internet-produced content, such as social networks and knowledge …

In the Relational Reinforcement learning framework, we propose an algorithm that learns an
action model allowing to predict the resulting state of each action in any given situation. The …

Abstract To date, Inductive Logic Programming (ILP) systems have largely assumed that all
data needed for learning have been provided at the onset of model construction …

This article presents Open the Chests, a novel benchmark environment designed for
simulating and testing activity recognition and reactive decision-making algorithms. By …

In the last decade, researchers have recognized the need of an increased attention to a type
of knowledge discovery applications where the data analyzed is not finite, but streams into …

Symbolic event recognition systems often rely on knowledge bases of event definitions,
expressed in first-order logic, to detect event occurrences over time. Logical frameworks for …

Handling relational data streams has become a crucial task, given the availability of
pervasive sensors and Internet-produced content, such as social networks and knowledge …