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Modular design patterns for hybrid learning and reasoning systems
2021
Applied intelligence (Boston)
AbstractThe unification of statistical (data-driven) and symbolic (knowledge-driven) methods is widely recognized as one of the key challenges of modern AI. Recent years have seen a large number of publications on such hybrid neuro-symbolic AI systems. That rapidly growing literature is highly diverse, mostly empirical, and is lacking a unifying view of the large variety of these hybrid systems. In this paper, we analyze a large body of recent literature and we propose a set of modular design
doi:10.1007/s10489-021-02394-3
fatcat:ecyruntfdncsbbtdglhllwc6vi