An artificial life environment for autonomous virtual agents with multi-sensorial and multi-perceptive features

Our approach is based on the multi-sensory integration of the standard theory of neuroscience, where signals of a single object coming from distinct sensory systems are combined. The acquisition steps of signals, filtering, selection and simplification intervening before proprioception, active and predictive perception are integrated into virtual sensors and a virtual environment. We will focus on two aspects: 1) the assignment problem: determining which sensory stimuli belong to the same virtual object and (2) the sensory recoding problem: recoding signals in a common format before combining them. We have developed three novel methodologies to map the information coming from the virtual sensors of vision, audition and touch as well as that of the virtual environment in the form of a 'cognitive map'. Copyright © 2004 John Wiley and Sons, Ltd

Automating content generation for large-scale virtual learning environments using semantic web services

The integration of semantic web services with three-dimensional virtual worlds offers many potential avenues for the creation of dynamic, content-rich environments which can be used to entertain, educate, and inform. One such avenue is the fusion of the large volumes of data from Wiki-based sources with virtual representations of historic locations, using semantics to filter and present data to users in effective and personalisable ways. This paper explores the potential for such integration, addressing challenges ranging from accurately transposing virtual world locales to semantically-linked real world data, to integrating diverse ranges of semantic information sources in a usercentric and seamless fashion. A demonstrated proof-of-concept, using the Rome Reborn model, a detailed 3D representation of Ancient Rome within the Aurelian Walls, shows several advantages that can be gained through the use of existing Wiki and semantic web services to rapidly and automatically annotate content, as well as demonstrating the increasing need for Wiki content to be represented in a semantically-rich form. Such an approach has applications in a range of different contexts, including education, training, and cultural heritage