Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
In this paper we implement planning using answer set programming. We consider the action language A and its extensions. We show that when the domain is described using richer feat...
Abstract. Classical planning domain representations assume all the objects from one type are exactly the same. But when solving problems in the real world systems, the execution of...
In this paper, we propose a new language-independent representation of adhoc constraints, called a box constraint collection. Using constructive disjunction, this representation ac...
We introduce a nonparametric representation for graphical model on trees which expresses marginals as Hilbert space embeddings and conditionals as embedding operators. This formul...