The Meaning of Semiochemicals to the Design of Self-Organizing Systems
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
In biology, many organisms coordinate their interactions in a self-organizing and emergent way solely by means of indirect communication based on chemical substances. These so-called semiochemicals comprise pheromones, mediating the coordination between organisms of the same species, as well as allelochemics, such as allomones, kairomones, synomones, and apneumones, mediating the coordination between organisms of different species. In order to exploit this biological diversity for the engineering of well adapted coordination mechanisms for self-organizing emergent multi-agent systems, the micro- and macroscopic effects of the different types of semiochemicals have to be better understood. In this paper, we analyze these effects and based on that provide design guidelines that identify appropriate types of digital semiochemicals to use for the interactions between agents on the local level in order to achieve certain required effects on the global level. We apply these guidelines within an existing engineering methodology and present as a result an iteratively refined model of a decentralized coordination mechanism well adapted for the solution of pickup and delivery problems by self-organizing emergent multi-agent systems.
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