Proceedings

NeSyA: Neurosymbolic Automata

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 5950-5958.

https://doi.org/10.24963/ijcai.2025/662

Abstract

Neurosymbolic (NeSy) AI has emerged as a promising direction to integrate

neural and symbolic reasoning. Unfortunately, little effort has been given

to developing NeSy systems tailored to sequential/temporal problems. We identify

symbolic automata (which combine the power of automata for temporal reasoning

with that of propositional logic for static reasoning) as a suitable formalism for

expressing knowledge in temporal domains. Focusing on the task of sequence classification

and tagging we show that symbolic automata can be integrated with neural-based

perception, under probabilistic semantics towards an end-to-end differentiable model.

Our proposed hybrid model, termed NeSyA (Neuro Symbolic

Automata) is shown to either scale or perform more accurately than previous

NeSy systems in a synthetic benchmark and to provide benefits in terms of generalization

compared to purely neural systems in a real-world event recognition task.

Code is available at: https://github.com/nmanginas/nesya

Nikolaos Manginas, George Paliouras, and Luc de Raedt. 2025. NeSyA: Neurosymbolic Automata. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 5950–5958. https://doi.org/10.24963/ijcai.2025/662
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