The Semantic Web Paradigm for a Real-Time Agent Control (Part I)

Mazilescu, Vasile (2010): The Semantic Web Paradigm for a Real-Time Agent Control (Part I).

Abstract

For the Semantic Web point of view, computers must have access to structured collections of information and sets of inference rules that they can use to conduct automated reasoning. Adding logic to the Web, the means to use rules to make inferences, choose courses of action and answer questions, is the actual task for the distributed IT community. The real power of Intelligent Web will be realized when people create many programs that collect Web content from diverse sources, process the information and exchange the results with other programs. The first part of this paper is an introductory of Semantic Web properties, and summarises agent characteristics and their actual importance in digital economy. The second part presents the predictability of a multiagent system used in a learning process for a control problem.

• Item Type: MPRA Paper
• Language: English
• Keywords: Semantic Web, agents, fuzzy knowledge, evolutionary computing
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C88 - Other Computer Software

References

Knapik M., Johnson J., Developing Intelligent Agents for Distributed Systems, McGraw Hill, 1998.

Wooldridge M., Jennings N.R., 1995. Proceedings of ECAI Workshop on Agent Theories, Architectures and Languages, pp. 1-32.

An introduction to ontologies: www. Semantic Web.org/knowmarkup.html

Simple HTML Ontology Extensions Frequently Asked Questions (SHOE FAQ): www.cs.umd.edu/projects/plus/SHOE/faq.html

DARPA Agent Markup Language (DAML) home page: www.daml.org/