Consensus Problem in High-Order Multiagent Systems With Lipschitz Nonlinearities and Jointly Connected Topologies
Why this work is in the frame
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Bibliographic record
Abstract
The leaderless consensus problem in a class of high-order multiagent systems with Lipschitz nonlinearities is studied in this paper. Despite existing leaderless consensus protocols devoted to high-order multiagent systems with Lipschitz nonlinearities, the proposed protocol in this paper guarantees achieving consensus in networks of agents with jointly connected topologies. To achieve this goal, first a consensus protocol for high-order multiagent systems with general linear models is proposed. By introducing a common Lyapunov candidate for the set of switching topologies and based on the Cauchy convergence criterion, achieving consensus under the proposed protocol is studied. Then, sufficient conditions are derived under which the results are extended to the case of Lipschitz nonlinearities in agents models. Numerical examples validate the proposed consensus protocol.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 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