Cooperative control for multi-target interception with sensing and communication limitations: A game-theoretic approach
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, the problem of multi-vehicle cooperative interception of moving objects with unknown arrival times, trajectories and dynamics is investigated. The vehicles are assumed to have limited sensing and communication ranges. Therefore, centralized approaches are not feasible, specially when there are a large number of vehicles and targets. A game theoretic cooperative receding horizon controller is proposed here to address this problem. The control design is based on the prediction of the future positions of targets with limited information, as well as a reward allocation policy for accomplishing the target interception tasks. To learn the optimal strategy in the resulting potential game, a state-of-the-art method, the generalized regret monitoring, is applied and its effectiveness is demonstrated by simulation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it