Mean-Field Control for Stochastic Delay Systems via Static Output Feedback Strategy
Bibliographic record
Abstract
In this paper, we consider mean-field control based on the static output feedback (SOF) strategy for stochastic delay systems. First, we define a stabilization problem via SOF gains in block-diagonal forms for systems with a single player, and then solve the problem of minimizing the upper bound of the cost function by cost-guaranteed cost control theory. For this problem, the necessary conditions for the sub-optimality are established using stochastic large-scale matrix equations. The obtained preliminary results are then used to study Pareto optimal strategies in cooperative games, for mean-field stochastic systems involving a large number of players. The primary contribution of this study is the derivation of a design method for decentralized strategies. Furthermore, a new low-order computational algorithm based on Newton's method is developed to obtain the decentralized strategy set. The cost degradation of the proposed decentralized SOF strategy set is then estimated. Finally, a simple numerical example is presented to demonstrate the usefulness and effectiveness of the proposed method. As a result, it is determined that the decentralized SOF strategy works well even when the number of players goes to infinity.
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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) | 0.001 | 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".