# A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems

arXiv: https://arxiv.org/abs/1905.12389 · HTML: https://mlsanity.com/paper/1905.12389/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 May 2019.

## Built on by (most cited first, 20 of 20)

- [Neuro-Symbolic Artificial Intelligence: Current Trends](https://mlsanity.com/paper/2105.05330/) (2021)
- [A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference](https://mlsanity.com/paper/2212.12393/) (2022)
- [Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases](https://mlsanity.com/paper/2102.11965/) (2021)
- [Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Review](https://mlsanity.com/paper/2202.12205/) (2022)
- [Neurosymbolic Diffusion Models](https://mlsanity.com/paper/2505.13138/) (2025)
- [Knowledge Engineering using Large Language Models](https://mlsanity.com/paper/2310.00637/) (2023)
- [ULLER: A Unified Language for Learning and Reasoning](https://mlsanity.com/paper/2405.00532/) (2024)
- [Defining neurosymbolic AI](https://mlsanity.com/paper/2507.11127/) (2025)
- [Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG](https://mlsanity.com/paper/2303.15113/) (2023)
- [The DeepLog Neurosymbolic Machine](https://mlsanity.com/paper/2508.13697/) (2025)
- [Modular Design Patterns for Hybrid Actors](https://mlsanity.com/paper/2109.09331/) (2021)
- [Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods](https://mlsanity.com/paper/2201.12126/) (2022)
- [Knowledge Affordances for Hybrid Human-AI Information Seeking](https://mlsanity.com/paper/2604.27539/) (2026)
- [Differentiable Fuzzy ALC: A Neural-Symbolic Representation Language for Symbol Grounding](https://mlsanity.com/paper/2211.12006/) (2022)
- [Teach Me How to Learn: A Perspective Review towards User-centered Neuro-symbolic Learning for Robotic Surgical Systems](https://mlsanity.com/paper/2307.03853/) (2023)
- [Mutual Understanding between People and Systems via Neurosymbolic AI and Knowledge Graphs](https://mlsanity.com/paper/2504.11200/) (2025)
- [Moral Decision-Making in Medical Hybrid Intelligent Systems: A Team Design Patterns Approach to the Bias Mitigation and Data Sharing Design Problems](https://mlsanity.com/paper/2102.11211/) (2021)
- [Commonsense Reasoning for Identifying and Understanding the Implicit Need of Help and Synthesizing Assistive Actions](https://mlsanity.com/paper/2202.11337/) (2022)
- [Standardizing Knowledge Engineering Practices with a Reference Architecture](https://mlsanity.com/paper/2404.03624/) (2024)
- [Ontology-Mediated Neurosymbolic Constraint Acquisition from Multiple Stakeholders](https://mlsanity.com/paper/2609.29876/) (2026)

## Abstract (arXiv)

We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns help to systematize the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature.