# Intelligent Software Web Agents: A Gap Analysis

arXiv: https://arxiv.org/abs/2102.06607 · HTML: https://mlsanity.com/paper/2102.06607/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 213 references that are in the map.
- First posted on arXiv 12 Feb 2021.

## Builds on (most cited first, 6 of 6)

- [Knowledge Graphs](https://mlsanity.com/paper/2003.02320/) (2020)
- [Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems](https://mlsanity.com/paper/1709.08071/) (2017)
- [Stability](https://mlsanity.com/paper/1310.0150/) (2013)
- [A ROS multi-ontology references services: OWL reasoners and application prototyping issues](https://mlsanity.com/paper/1706.10151/) (2017)
- [The LDBC Social Network Benchmark](https://mlsanity.com/paper/2001.02299/) (2020)
- [A Review of Platforms for the Development of Agent Systems](https://mlsanity.com/paper/2007.08961/) (2020)

## Built on by (most cited first, 2 of 2)

- [Modular Design Patterns for Hybrid Actors](https://mlsanity.com/paper/2109.09331/) (2021)
- [Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination](https://mlsanity.com/paper/2310.19503/) (2023)

## Abstract (arXiv)

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.