ROCS 2.0: An Integrated Temporal Logic Control Synthesis Tool for Nonlinear Dynamical Systems
Bibliographic record
Abstract
This paper introduces ROCS 2.0, a control synthesis tool for nonlinear systems with control objectives given as temporal logic formulas. In addition to the basic invariance, reachability, Büchi, and co-Büchi specifications that can be handled in the previous version of ROCS, ROCS 2.0 provides a major upgrade to support the general class of linear temporal logic formulas that can be translated to deterministic Büchi automata. Moreover, ROCS 2.0 not only maintains and accelerates the kernel of its previous version—the engine based on the specification-guided control method—by more efficient implementation, but also integrates a second engine that implements the abstraction-based control method, which is optimized to gain time and memory efficiency. Such a feature gives the user the freedom to choose the control synthesis method that is more suitable for a specific control problem.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".