ORCID iD
Jaimini: https://orcid.org/0000-0002-1168-0684
Document Type
Article
Abstract
Causal Neuro-Symbolic AI combines the benefits of causality with Neuro-Symbolic Artificial Intelligence (NeSyAI). More specifically, it (1) enriches NeSyAI systems with explicit representations of causality, (2) integrates causal knowledge with domain knowledge, and (3) enables the use of NeSyAI techniques for causal AI tasks. The explicit causal representation yields insights that predictive models may fail to analyze from observational data. It can also assist people in decision-making scenarios where discerning the cause of an outcome is necessary to choose among various interventions.
Publication Info
Postprint version. Published in IEEE Intelligent Systems, Volume 39, Issue 2, 2024.
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APA Citation
Jaimini, U., Henson, C., & Sheth, A. (2024). Causal Neuro-Symbolic AI: A synergy between Causality and Neuro-Symbolic methods. IEEE Intelligent Systems, 39(2).