Formal Description Techniques for CSPs and TCSPs.
Bibliographic record
Abstract
LOTOS is a formal specification technique for describing and verifying complex systems. In this paper, we investigate the applicability of LOTOS to specify and solve Constraint Satisfaction Problems (CSPs) as well as Temporal Constraint Satisfaction Problems (TCSPs). A CSP is a general framework used to represent and solve a large variety of combinatorial problems including frequency assignment, configuration and conceptual design, network management and transportation. A TCSP is one particular case of CSPs, where constraints are temporal relations between temporal variables defined over a set of time intervals. TCSPs are used to handle problems involving temporal constraints such as scheduling, planning and computational linguistics. Through simulation and model-checking verification, we show, in this paper, how to solve CSPs and TCSPs using LOTOS specifications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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 source (direct Gemma or distilled Codex), 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".