Automated planning can be used to efficiently recognize goals and plans from partial or full
observed action sequences. In this paper, we propose goal recognition heuristics that rely …

Recent approaches to goal recognition have progressively relaxed the requirements about
the amount of domain knowledge and available observations, yielding accurate and efficient …

Recognising the goal of an agent from a trace of observations is an important task with many
applications. The state-of-the-art approach to goal recognition (GR) relies on the application …

There is huge demand for robots to work alongside humans in heterogeneous teams. To
achieve a high degree of fluidity, robots must be able to (1) recognize their human co …

Computer-based human activity recognition of daily living has recently attracted much
interest due to its applicability to ambient assisted living. Such applications require the …

Plan recognition algorithms output hypotheses about an agent's plans from its observed
actions. Due to imperfect knowledge about the agent's behavior and the environment, it is …

This article provides new techniques for optimizing domain design for goal and plan
recognition using plan libraries. We define two new problems: Goal Recognition Design for …

A known limitation of many diagnosis algorithms is that the number of diagnoses they return
can be very large. This is both time consuming and not very helpful from the perspective of a …

Devising models that reliably recognize player goals is a key challenge in creating player-
adaptive games. Player goal recognition is the task of automatically recognizing the intent of …

We present a knowledge representation framework on the basis of the Event Calculus that
allows an agent to recognize complex activities from low‐level observations received by …