Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
In this paper we present the basic requirements and initial design of a system which manages and facilitates changes to an OWL ontology in a multi-editor environment. This system u...
Timothy Redmond, Michael Smith, Nick Drummond, Tan...
An emerging tapestry of computations will soon integrate systems around the globe. It will evolve without central control. Its complexity will be vast. We need new ideas, tools an...
Design aspects and software modelling for ubiquitous real-time camera system are described in this paper. We propose system architecture using a network of inexpensive cameras and...
Chang Hong Lin, Wayne Wolf, Andrew Dixon, Xenofon ...