What question did this study set out to answer?

To present a neuro-symbolic algorithm that enhances reasoning through deterministic mechanisms and semantic fields.

June 15, 2026Open Access

Deterministic Artificial Intelligence Algorithm – a hybrid neuro-symbolic architecture based on semantic fields, fuzzy logic, and predicative notation.

Key Points

To present a neuro-symbolic algorithm that enhances reasoning through deterministic mechanisms and semantic fields.
Developed a neuro-symbolic architecture integrating fuzzy logic and predicative notation.
Limited the role of large language models (LLMs) to generative and interpretive layers.
Focused on ensuring reproducibility and auditability of the reasoning process.
Achieved a significant reduction in false information generation.
Maintained the naturalness of dialogue during interactions.
Ensured complete auditability of the decision-making process.

Abstract

This article presents an innovative neuro-symbolic approach that processes logical structures and semantic fields built using fuzzy logic. The presented algorithm limits the LLM's role exclusively to the generative and interpretive layers, while the core of reasoning is a deterministic mechanism based on semantic fields, fuzzy logic and predicative notation. Such a solution ensures full process auditability, reproducibility of results, and a drastic reduction in the risk of generating false information, while preserving the naturalness of the dialogue.

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