A Robust Controlled Backward Reach Tube with (Almost) Analytic Solution for Two Dubins Cars
Why this work is in the frame
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Bibliographic record
Abstract
Benchmark Proposal: We describe how a well-known backward reachability problem with nonlinear dynamics and adversarial inputs—based on a pursuit evasion game with two identical vehicles that have Dubins car dynamics—can be viewed as a robust controlled backward reach tube. The resulting set is nonconvex with a surface that is nondifferentiable in places, yet (mostly explicit) closed form solutions for points on the surface of this set have been derived based on a classical differential game analysis, and so these points can be sampled with high accuracy at arbitrary density. We propose this problem as a benchmark because few existing reachability algorithms can tackle robust controlled backward reach tubes despite their potential for proving the robust safety of systems, and this (almost) analytic solution exists against which to compare prospective solutions. We then describe some extensions to the problem to provide additional future challenges. Code is provided.
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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 | 0.000 | 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 it