A new hybrid task sharing method for cooperative multi agent systems
Bibliographic record
Abstract
In this paper, we discuss a novel method for task sharing and cooperation between Firefighter Agents in Roborescue simulation environment. This method consists of three main sections, which has an effect on the agents' decision-making process, based on various parameters. The first section is the selection of agent's individual goal. The second section is the supervision of the fire hall center. The aim of this section is the supervision of the center on selecting goals by firefighters, arranging the firefighter groups and producing appropriate advice for guiding the groups' activities into optimal solution. The third section is selecting the group's goal by cooperation with other group's members. The results have been assessed from different viewpoints such as primary reaction speed, number of passed messages and final score based on T-Test statistical distribution. Overall, this method has better results in comparison with the usual reactive, distributed, and centralized task allocation methods. There are some important advantages to this method such as appropriate primary reaction speed, robustness to destruction of some agents or center, robustness to limited communication and higher final score
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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".