Holonic self-organization of multi-agent systems by fuzzy modeling with application to intelligent manufacturing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Holonic manufacturing aims to design standardized, modular manufacturing systems made of interchangeable parts, to enable flexibility, online reconfigurability and self-organizing capabilities for the production systems. Recent advances in distributed artificial intelligence and networking technologies have proven that theoretical multi-agent systems (MAS) concepts are very suitable for the real life implementation of holonic concepts. Building on our recent results in the design and implementation of holonic reconfigurable architectures, the paper introduces a novel approach to the online self-organization of distributed systems. By using fuzzy set and uncertainty theoretical concepts, we construct a mathematical foundation for modeling MAS, where appropriate holonic structures are identified for each particular application. This approach opens new possibilities for the design of any distributed system that needs self-organization as an intrinsic property.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it