Planning collision-free paths for multiple robots traversing a shared space is a problem that grows combinatorially with the number of robots. The naive centralised approach soon ...
Abstract. Many sophisticated classification algorithms have been proposed. However, there is no clear methodology of comparing the results among different methods. According to ou...
In recent years, there has been a cross-fertilization of ideas between computational neuroscience models of the operation of the neocortex and artificial intelligence models of mac...
John Thornton, Jolon Faichney, Michael Blumenstein...
Data anonymization techniques based on enhanced privacy principles have been the focus of intense research in the last few years. All existing methods achieving privacy principles ...
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
Abstract. This paper presents a formulation of an optimality principle for a new class of concurrent decision systems formed by products of deterministic Markov decision processes ...
When a user is looking for a product recommendation they usually lack expert knowledge regarding the items they are looking for. Ontologies on the other hand are crafted by experts...
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Learning Classifier System (LCS) is an effective tool to solve classification problems. Clustering with XCS (accuracy-based LCS) is a novel approach proposed recently. In this pape...
Abstract. We describe a probabilistic reference disambiguation mechanism developed for a spoken dialogue system mounted on an autonomous robotic agent. Our mechanism performs proba...