Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases

02/23/2021
by   Michael van Bekkum, et al.
0

The unification of statistical (data-driven) and symbolic (knowledge-driven) methods is widely recognised as one of the key challenges of modern AI. Recent years have seen large number of publications on such hybrid neuro-symbolic AI systems. That rapidly growing literature is highly diverse and mostly empirical, and is lacking a unifying view of the large variety of these hybrid systems. In this paper we analyse a large body of recent literature and we propose a set of modular design patterns for such hybrid, neuro-symbolic systems. We are able to describe the architecture of a very large number of hybrid systems by composing only a small set of elementary patterns as building blocks. The main contributions of this paper are: 1) a taxonomically organised vocabulary to describe both processes and data structures used in hybrid systems; 2) a set of 15+ design patterns for hybrid AI systems, organised in a set of elementary patterns and a set of compositional patterns; 3) an application of these design patterns in two realistic use-cases for hybrid AI systems. Our patterns reveal similarities between systems that were not recognised until now. Finally, our design patterns extend and refine Kautz' earlier attempt at categorising neuro-symbolic architectures.

READ FULL TEXT

page 7

page 12

page 13

research
09/20/2021

Modular Design Patterns for Hybrid Actors

Recently, a boxology (graphical language) with design patterns for hybri...
research
05/29/2019

A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems

We propose a set of compositional design patterns to describe a large va...
research
06/09/2022

Modular design patterns for neural-symbolic integration: refinement and combination

We formalise some aspects of the neural-symbol design patterns of van Be...
research
08/26/2022

Learning and Compositionality: a Unification Attempt via Connectionist Probabilistic Programming

We consider learning and compositionality as the key mechanisms towards ...
research
03/09/2020

Neuro-symbolic Architectures for Context Understanding

Computational context understanding refers to an agent's ability to fuse...
research
04/13/2023

Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model-based AI Systems

The release of ChatGPT, Bard, and other large language model (LLM)-based...

Please sign up or login with your details

Forgot password? Click here to reset