Bibliographic record
Abstract
This paper presents a multi-agent system architecture developed to track moving objects. This architecture consists of several software agents with similar architecture and functions. An object can move freely within a predefined area, which is divided into several sub-areas based on the number of agents used in the system. Each agent is responsible for a specified sub-area. Agents are able to communicate with each other and to coordinate their activities by sharing their knowledge about the position of the moving object. Global Positioning Systems (GPS) are utilized to locate the exact position of the moving object. A GPS receiver is placed inside the moving object and serves as a signal platform that provides the desired information about its location to each agent. The main purpose of this work is to develop agents that are able to interact with the users, who are interesting in tracking some objects, and to provide them with the exact position of a moving object. This paper provides the agents' architecture, design and implementations that enable them to cooperate and communicate with each other to track a moving object. A prototype is implemented, using the ZEUS toolkit.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".