A Multiagent Geosimulation Approach for Intelligent Sensor Web Management
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
A Sensor Web (SW) consists of a large collection of small nodes providing collaborative and distributed sensing abilities in unpredictable environments. Nodes composing such an SW are characterized by resource restrictions, especially energy, processing power, and communication capacities. A sensor web can be thought of as a spatially and functionally distributed complex system evolving in and interacting with a geographic environment. So far, the majority of the currently deployed SWs has been mainly used for prototyping purposes. These SWs operate without considering a management scheme and do not take into account the geographic environment characteristics in which they are deployed. Multiagent Geosimulation (MAGS) is a recent modeling and simulation paradigm which provides a flexible approach that can be used to analyze complex systems such as SW in large-scale and complex georeferenced environments. In this paper, we propose to use an MAGS approach to support SW management. Moreover, we present Sensor-MAGS, a multiagent geosimulation system which manages sensor nodes using Informed Virtual Geographic Environments (IVGE). This system is applied in the context of a water resource monitoring project.
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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 | 0.001 | 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