Formation-containment control using dynamic event-triggering mechanism for multi-agent systems
Why this work is in the frame
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Bibliographic record
Abstract
The paper proposes a novel approach for formation-containment control based on a dynamic event-triggering mechanism for multi-agent systems. The leader-leader and follower-follower communications are reduced by utilizing the distributed dynamic event-triggered framework. We consider two separate sets of design parameters: one set comprising control and dynamic event-triggering parameters for the leaders and a second set similar to the first one with different values for the followers. The proposed algorithm includes two novel stages of co-design optimization to simultaneously compute the two sets of parameters. The design optimizations are convex and use the weighted sum approach to enable a structured trade-off between the formation-containment convergence rate and associated communications. Simulations based on non-holonomic mobile robot multi-agent systems quantify the effectiveness of the proposed approach.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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