Integrating Base Object Model Components into DEVS-based Simulation
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
The SISO standard Base Object Model (BOM) specification facilitates interoperability, re-usability, and composability of component models for simulation purposes. The common practice of constructing a BOM-based simulation system using the High-Level Architecture (HLA) does not, however, exploit the hierarchy of BOM components and hence limits re-usability. The Discrete EVent system Specification (DEVS) formalism has proven to be appropriate for hierarchical modeling and subsequent parallel and distributed simulation. In this paper we integrate the key part of the BOM, the component kernel, into a DEVS framework by mapping it onto atomic DEVS models. On the one hand, this precisely defines an automated mapping which fully conserves the wealth of information (such as hierarchy) present in BOMs. On the other hand, it allows for re-use of a plethora of theory, techniques and tools available for the DEVS formalism. If necessary, the DEVS models obtained through the integration can be optimized. A small case study of the take-off and landing of a plane demonstrates the increased re-usability compared to HLA-based approaches. This case study is also used to compare the performance of a BOM-based simulation system with the DEVS equivalent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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