Pattern-based engineering of Neurosymbolic AI Systems

The symbiotic combination of sub-symbolic and symbolic AI techniques is a significant trend in AI, leading to the fast-paced development of various techniques that integrate these paradigms to build intelligent systems. However, the wealth of heterogeneous architectural options for combining the paradigms into Neurosymbolic AI (NeSy-AI) systems poses significant challenges. In particular, there is currently no standardized way to design, engineer, and document such systems that encompass visual and formal notations. Existing works aim to address this challenge by systematically modelling NeSy-AI systems as design patterns that include process, data, and human interactions. However, these works focus on capturing specific views of the system rather than aiming to support the broad process of AI system engineering. This paper outlines a vision of pattern-based AI Systems engineering, aiming to support the engineering process of NeSy-AI systems with tasks such as system documentation and artefact generation through interlinked visual and formal notations with Knowledge Graphs at its core.

Authors

Institutions

Publication Details

Journal
Journal of Web Semantics
Published
2024-12-27
DOI
https://doi.org/10.1016/j.websem.2024.100855
Citations
3
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
1.04

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pattern-based engineering of Neurosymbolic AI Systems

Fajar J. Ekaputra
3 citations
Journal of Web Semantics
Neural Networks and Applications
1.04
article

Pattern-based engineering of Neurosymbolic AI Systems

Fajar J. Ekaputra
article en
3 citations

Abstract

The symbiotic combination of sub-symbolic and symbolic AI techniques is a significant trend in AI, leading to the fast-paced development of various techniques that integrate these paradigms to build intelligent systems. However, the wealth of heterogeneous architectural options for combining the paradigms into Neurosymbolic AI (NeSy-AI) systems poses significant challenges. In particular, there is currently no standardized way to design, engineer, and document such systems that encompass visual and formal notations. Existing works aim to address this challenge by systematically modelling NeSy-AI systems as design patterns that include process, data, and human interactions. However, these works focus on capturing specific views of the system rather than aiming to support the broad process of AI system engineering. This paper outlines a vision of pattern-based AI Systems engineering, aiming to support the engineering process of NeSy-AI systems with tasks such as system documentation and artefact generation through interlinked visual and formal notations with Knowledge Graphs at its core.

Journal of Web SemanticsVol. 85
Vienna University of Economics and Business (AT)
Austrian Science Fund, Österreichische Forschungsförderungsgesellschaft, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 18%
Neural Networks and Applications
1.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.