We introduce a new type of arrow in the update frames (or “action models”) of Dynamic Epistemic Logic in a way that enables us to reason about epistemic temporal dynamics in m...
This paper describes methods for collecting user activity data in a peer production educational system, the Instructional Architect (IA), and then takes a social network perspectiv...
In categorial systems with a fixed structural component, the learning problem comes down to finding the solution for a set of typeassignment equations. A hard-wired structural co...
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...