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

@article{Bekkum2021ModularDP,
  title={Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases},
  author={Michael A. van Bekkum and Maaike de Boer and F. V. Harmelen and Andr{\'e} Meyer-Vitali and Annette ten Teije},
  journal={Appl. Intell.},
  year={2021},
  volume={51},
  pages={6528-6546}
}
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… 
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