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Accepted Papers
The Needed Bridge Connecting Symbolic and Sub-symbolic AI

Maikel Leon, Department of Business Technology, Miami Herbert Business School, University of Miami, Florida, USA

ABSTRACT

Innovations that combine the interpretability of symbolic AI with the learning capabilities of sub-symbolic AI can flourish in the nexus of symbolic and sub-symbolic AI. This research presents Fuzzy Cognitive Maps (FCMs). This hybrid model combines the best features of both paradigms as a workable answer to the problems of interpretability and explainability in artificial intelligence (AI) systems. FCMs have become a robust framework for logically and intuitively supporting decision-making processes and expressing causal information. A more organic and adaptable problem-solving approach is made possible by FCMs’ ability to manage the inherent ambiguity and uncertainty present in real-world situations. Because of their innate flexibility and ability to learn and adapt from sub-symbolic AI, FCMs are an excellent fit for applications requiring high interpretability and explainability.

KEYWORDS

Fuzzy Cognitive Maps, Symbolic AI, and Sub-symbolic AI.





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