Discoverable Agent Knowledge -- A Formal Framework for Agentic KG Affordances (Extended Version)
The article presents a formal framework for understanding agentic knowledge graph (KG) affordances. It critiques existing KG metadata standards for lacking insights into what agents can derive from KGs. The authors propose a new semantic layer, the Agentic Affordance Profile (AAP), to enhance KG selection and composition.
- ▪The paper critiques current KG metadata standards like VoID and DCAT for not addressing agent-specific knowledge extraction.
- ▪It introduces the Agentic Affordance Profile (AAP) as a solution for better KG selection and failure diagnosis.
- ▪A five-point research agenda is outlined to advance AAP-based affordance matching.
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Computer Science > Artificial Intelligence arXiv:2605.19186 (cs) [Submitted on 18 May 2026] Title:Discoverable Agent Knowledge -- A Formal Framework for Agentic KG Affordances (Extended Version) Authors:Terry R. Payne, Valentina Tamma, Enrico Daga View a PDF of the paper titled Discoverable Agent Knowledge -- A Formal Framework for Agentic KG Affordances (Extended Version), by Terry R. Payne and 1 other authors View PDF HTML (experimental) Abstract:Two decades ago, the Semantic Web Services community was asked how agents with different ontological commitments could discover, compose, and invoke web services coherently.
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