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July 31, 2026Open Access

S-AI-RLM: A Recursive Logic Machine

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Authors

SSSaid Slaoui

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Overview

Randomized trial demonstrates 100% decidability and over 84% accuracy in AI systems, suggesting a new framework for intelligent architecture.

Key Points

  • This work aims to develop a unified AI architecture that ensures termination, logical correctness, and stability.
  • Introduced S-AI-RLM with a recursive symbolic core, hormonal regulation, and a triadic metacognitive regime.
  • Realized through twelve agents across three functional layers, using a large language model.
  • Established global asymptotic stability via Lyapunov arguments.
  • Achieved a decidability rate of 100% and decision accuracy exceeding 84%.
  • Demonstrated monotonic entropy reduction and a frugality index of at least 0.71.
  • Validated across four standard reasoning benchmarks against four reference systems.

Cite This Study

Said Slaoui (2026) studied this question.

synapsesocial.com/papers/6a6c4702747664a1aa73c060https://doi.org/10.5281/zenodo.21683805
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