Andrea Agiollo, Enkeleda Bardhi, Giovanni Ciatto, Giovanni Dumancic, Giuseppe Marra (a cura di)
ANSyA 2025: Advanced Neuro-Symbolic Applications, pp. 84–92
CEUR Workshop Proceedings 4125
CEUR-WS
ottobre 2025
In neuro-symbolic AI (NeSy), integrating symbolic languages – typically subsets of first-order logic (FOL) –, with neural networks (NNs) serves goals like enhancing symbolic processing, extending reasoning with pattern recognition, and guiding neural learning with symbolic knowledge—a.k.a. symbolic knowledge injection (SKI). Despite its utility, FOL’s expressiveness poses challenges to SKI algorithms, and its general-purpose nature complicates use for non-experts. We propose SKI-lang, a domain-specific language for SKI that balances practicality, clear semantics, and expressiveness–tractability trade-offs. SKI-lang simplifies symbolic specification, serves as a unified interface for diverse SKI approaches, and allows for automating benchmarks from NeSy literature. We discuss the design choices behind SKI-lang and its implementation, and demonstrate its effectiveness and versatility through a few case studies.
parole chiave
symbolic knowledge injection, SKI-lang, NeSy, language, Python
evento origine
rivista o collana
progetto finanziatore
FAIR-PE01-SP08 — Future AI Research – Partenariato Esteso sull'Intelligenza Artificiale – Spoke 8 “Pervasive AI”
(01/01/2023–31/12/2025)
ANSyA 2025 @ ECAI-2025
CEUR Workshop Proceedings (CEUR-WS.org)