4 papers · 1 filter
A*Net and NBFNet Learn Negative Patterns on Knowledge Graphs
Patrick Betz, Nathanael Stelzner, Christian Meilicke +2
In this technical report, we investigate the predictive performance differences of a rule-based approach and the GNN architectures NBFNet and A*Net with respect to knowledge graph…
Fact Probability Vector Based Goal Recognition
Nils Wilken, Lea Cohausz, Christian Bartelt +1
We present a new approach to goal recognition that involves comparing observed facts with their expected probabilities. These probabilities depend on a specified goal g and initial…
Leveraging Planning Landmarks for Hybrid Online Goal Recognition
Nils Wilken, Lea Cohausz, Johannes Schaum +3
Goal recognition is an important problem in many application domains (e.g., pervasive computing, intrusion detection, computer games, etc.). In many application scenarios it is imp…
Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition
Nils Wilken, Lea Cohausz, Johannes Schaum +2
An important feature of pervasive, intelligent assistance systems is the ability to dynamically adapt to the current needs of their users. Hence, it is critical for such systems to…