Impulsive Consensus of Networked Multi-Agent Systems With Distributed Delays in Agent Dynamics and Impulsive Protocols
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Bibliographic record
Abstract
This paper studies the consensus problem of networked multi-agent systems (NMASs). Distributed delays are considered in the agent dynamics, and we propose a new type of impulsive consensus protocols that also takes into account of distributed delays. A novel method is developed to estimate the relation between the agent states at the impulsive instants and the distributed-delayed agent states, which helps to use the Razumikhin-type stability result to investigate the consensus of NMASs with distributed-delayed impulses. Sufficient conditions are established to guarantee that the network consensus can be reached via the proposed consensus protocols with fixed and switching topologies, respectively. Numerical simulations are also provided to demonstrate our theoretical results.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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