Planning for complex systems lacks the convergence metrics and defect detection that manufacturing achieved through six decades of statistical process control. FDRP addresses this gap by treating each planning decision as a manufactured artifact with measurable convergence and gate-reviewed quality, applying SPC, 5S, RAMS, Andon, and configuration freeze directly to planning. Applied across 58 production runs (1,279 decisions), the system's strongest empirical contribution is the antimatter building programme: 68 LLM-generated expert specialists across two rounds produced 28,936 lines of analysis and 1,656 structured findings, discovering expert persistence as an emergent operational pattern. Cross-model verification with 3 independent LLMs revealed 4 systematic bias patterns, suggesting that N≥3 models are needed for blind spot detection. Cross-domain validation on earthquake seismology and power grid data provides preliminary evidence that the sparse-principle thesis generalises. We propose progressive disclosure as the unifying architecture—a hypothesis under test.
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Abstract
Table of Contents
Act I: The Framework
- Introduction: The Planning Quality Gap
- Related Work and Theoretical Foundations
- Architecture: FDRP as Manufacturing System
- The Convergence Velocity Tensor
- Progressive Disclosure as Unifying Principle
Act II: The Evidence
- Production Dataset: 58 Runs Across 3 Domains
- Case Study: Antimatter Building Programme
- Case Study: Asymmetric Cyber Defence
- Case Study: Fire Crisis Response
- Cross-Model Verification
- Cross-Domain Validation
- Expert Expansion and Persistence
- Bias Detection and Mitigation
- Statistical Analysis and Control Charts
Act III: The Reflection
- Limitations and Threats to Validity
- The Self-Correction Thesis
- Future Directions
- Conclusion
Cite This Work
BibTeX
@article{olos2026fdrp,
title = {FDRP: A Self-Evolving Architecture for Planning Quality},
author = {Olos, L.},
year = {2026},
note = {Preprint},
url = {https://fdrp.liviu.ai/paper/FDRP-Paper-v14.pdf}
}
APA (7th edition)
Olos, L. (2026). FDRP: A Self-Evolving Architecture for Planning Quality. Preprint. https://fdrp.liviu.ai/paper/FDRP-Paper-v14.pdf
Chicago (17th edition)
Olos, L. “FDRP: A Self-Evolving Architecture for Planning Quality.” Preprint, 2026. https://fdrp.liviu.ai/paper/FDRP-Paper-v14.pdf
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