Intelligent Software Web Agents: A Gap Analysis

Abstract

Semantic web technologies have shown their effectiveness, especially when it comes to knowledge representation, reasoning, and data integrations. However, the original semantic web vision, whereby machine readable web data could be automatically actioned upon by intelligent software web agents, has yet to be realised. In order to better understand the existing technological challenges and opportunities, in this paper we examine the status quo in terms of intelligent software web agents, guided by research with respect to requirements and architectural components, coming from that agents community. We start by collating and summarising requirements and core architectural components relating to intelligent software agent. Following on from this, we use the identified requirements to both further elaborate on the semantic web agent motivating use case scenario, and to summarise different perspectives on the requirements when it comes to semantic web agent literature. Finally, we propose a hybrid semantic web agent architecture, discuss the role played by existing semantic web standards, and point to existing work in the broader semantic web community any beyond that could help us to make the semantic web agent vision a reality.