Immune System-Inspired Dynamic Multi-Robot Coordination
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 investigates multi-robot coordination for the deployment of autonomous mobile robots in order to carry out a specific task. A key to utilizing of the full potential of cooperative multi-robot systems is effective and efficient multi-robot coordination. The paper presents a novel method of multi-robot coordination based on an Artificial Immune System. The developed approach relies on Jern’s Immune Network Theory, which concerns how an antibody stimulates or suppresses another antibody and recognizes non-self antigens. In the present work, the robots are analogous to antibodies and the robotic task is analogous to an antigen in a biological immune system. Furthermore, stimulation and suppression in an immune system correspond to communication among robots. The artificial immune system will select the appropriate number of antibodies autonomously to eliminate the antigens. The developed method of multirobot coordination is verified by computer simulation.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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