Intelligent Software Web Agents: A Gap Analysis

TL;DR

This paper analyzes the current state of intelligent software web agents, identifying gaps between semantic web technologies and their practical, automated application, and proposes a hybrid architecture to address these challenges.

Contribution

It introduces a hybrid semantic web agent architecture and discusses how it aligns with existing standards and future research opportunities.

Findings

Identified key requirements for intelligent web agents.

Proposed a hybrid architecture integrating semantic web standards.

Highlighted open challenges and future research directions.

Abstract

Semantic web technologies have shown their effectiveness, especially when it comes to knowledge representation, reasoning, and data integration. 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 opportunities and challenges, 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 the agents community. 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 from the semantic web agent literature. We subsequently propose a hybrid semantic web agent architecture, and use the various components and subcomponents in order to provide a focused discussion in relation to existing semantic web standards and community activities. Finally, we highlight open research opportunities and challenges and take a broader perspective of the research by discussing the potential for intelligent software web agents as an enabling technology for emerging domains, such as digital assistants, cloud computing, and the internet of things.