Implementation of a subsumption based architecture using model-driven development
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
This paper describes the implementation of a subsumption architecture by using Model Driven Development in a real-time physical platform. The behaviours are implemented as finite state-machines and are guaranteed to be executed in real-time while avoiding deadlocks. The platform used is compatible with Robot Operating System, which is becoming the de facto standard for robotics applications nowadays. The sensors used for supporting the behaviours implemented are a Light Detection and Ranging and an Inertial Measurement Unit. The main contribution of this paper is in experimentally demonstrating a functional implementation, using Model Driven Development, of a multi-layer subsumption based autonomous robotics control. The paper shows, through experimentation, that the implementation of the architecture is reliable and efficient. With the success of the implementation in one platform, future development of subsumption in multiple platforms may be tried.
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 | 0.000 | 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