In the semantic web vision, data and information on the Web are
defined and linked so that they are both human readable and
machine understandable. Machine understandability means that
the data have been explicitly prepared for programs and
software agents to reason about and reuse. However, most
software agents have not been designed to run in a web
environment: the agents and web components are working in
different models. For example, most software agent frameworks
and tools do not support reasoning over content expressed in a
mixture of several ontologies. Web components, on the other
hand, lack notions of autonomy and a rich message-oriented
communication. This thesis suggests adding to a semantic web
site a dedicated service agent, capable of understanding the
ontologies used by the site and answering queries about the
content found on the site. Semantic web tasks are accomplished
by the cooperation of personal agents, service agents, and
semantic web servers. The semantic web language OWL is used as
the agent content language for message passing and
interaction. The F-OWL inference engine has been developed to
manage logical sentences explicitly stated in the web documents
as well as those that can be inferred. Within this thesis a
Trading Agent System (TAGA) running in the open Agentcities
platform, is used to support the hypothesis and demonstrate how
the software agent and semantic web paradigms can be
integrated.
We see two main contributions in our work. First, this thesis
explores the agent's roles in the service-based semantic web
and analyzes how agents and semantic web components can be
profitably integrated. Secondly, TAGA provides a flexible and
rich environment for simulating agent-based trading in dynamic
markets. The enhanced semantic web vision we present is that
both human and agents can directly access semantically marked
web pages through web interface; an agent can access other
agents by exchanging messages in an appropriate agent
communication language; personal agents and service agents
work together to understand the semantic web content, automate
web services and better serve humans.
Committee Members:
- Dr. Tim Finin (Chairperson)
- Dr. Marie desJardins
- Dr. James Hendler
- Dr. Anupam Joshi
- Dr. Charles Nicholas
- Dr. Yun Peng
Academic Advisor: Dr. Tim Finin
UMBC ebiquity