Semantic Web and Software Agents -- A Forgotten Wave of Artificial Intelligence?

TL;DR

The paper tackles the problem that AI history often centers on deep learning and LLMs, overlooking the Semantic Web’s knowledge-representation lineage and its synergy with Software Agents. It adopts a bibliometric and historical synthesis approach, normalizing AI hype cycles to identify a forgotten wave from 2000–2010. Findings suggest that the Semantic Web contributed foundational standards (RDF, OWL, SPARQL) and the concept of intelligent agents, with influence persisting in modern AI through knowledge graphs, retrieval-augmented generation, and neuro-symbolic methods, despite being labeled an AI winter. The work argues that reintegrating this wave into AI history provides actionable insights for integrating semantic technologies with current autonomous AI systems, emphasizing trust, provenance, and cryptographic proofs for trustworthy agents.

Abstract

The history of Artificial Intelligence (AI) is a narrative of waves -- rising optimism followed by crashing disappointments. AI winters, such as the early 2000s, are often remembered as barren periods of innovation. This paper argues that such a perspective overlooks a crucial wave of AI that seems to be forgotten: the rise of the Semantic Web, which is based on knowledge representation, logic, and reasoning, and its interplay with intelligent Software Agents. Fast forward to today, and ChatGPT has reignited AI enthusiasm, built on deep learning and advanced neural models. However, before Large Language Models (LLMs) dominated the conversation, another ambitious vision emerged -- one where AI-driven Software Agents autonomously served Web users based on a structured, machine-interpretable Web. The Semantic Web aimed to transform the World Wide Web into an ecosystem where AI could reason, understand, and act. Between 2000 and 2010, this vision sparked a significant research boom, only to fade into obscurity as AI's mainstream narrative shifted elsewhere. Today, as LLMs edge toward autonomous execution, we revisit this overlooked wave. By analyzing its academic impact through bibliometric data, we highlight the Semantic Web's role in AI history and its untapped potential for modern Software Agent development. Recognizing this forgotten chapter not only deepens our understanding of AI's cyclical evolution but also offers key insights for integrating emerging technologies.