Merging Intelligent Agency and the Semantic Web

Publication Type:
Conference Proceeding
27th International Conference on Innovative Techniques and Applications of Artificial Intelligence, 2007, pp. 197 - 210
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2007000955.pdf1.15 MB
Adobe PDF
The semantic web makes unique demands on agency. Such agents should: be built around an ontology and should take advantage of the relations in it, be based on a grounded approach to uncertainty, be able to deal naturally with the issue of semantic alignment, and deal with interaction in a way that is suited to the co-ordination of services. A new breed of `information-based intelligent agents [1] meets these demands. This form of agency is founded on ideas from information theory, and was inspired by the insight that interaction is an information revelation and discovery process. Ontologies are fundamental to these agents reasoning that relies on semantic distance measures. They employ entropy-based inference, a form of Bayesian inference, to manage uncertainty that they represent using probability distributions. Semantic alignment is managed through a negotiation process during which the agents uncertain beliefs are continually revised. The co-ordination of services is achieved by modelling interaction as time-constrained, resource-constrained processes a proven application of agent technology. In addition, measures of trust, reputation, and reliability are unified in a single model.
Please use this identifier to cite or link to this item: