Macro control languages and decision procedures for COCOLOG
Bibliographic record
Abstract
The control of a discrete event system is handled in the COCOLOG logic control system by use of an extra-logical representation of the control laws in terms of conditional control rules; these are condition-action pairs in which the conditions are mutually exclusive and exhaustive formulas in the language (L/sub k/) at the instant k. Such formulas are tested for deducibility from Th/sub k/, the current control theory, and once the unique deducible formula is found, the associated control action is applied to the system. The simplicity of L/sub k/ leads to even the most basic concepts having a complex expression as well formed formulas in L/sub k/. Furthermore, the triggering of elementary control actions often depends upon complex nested sets of conditional control formulas expressed in L/sub k/. In response to this set of problems, this article presents the foundations for: 1) a theory of the expression of complex predicates and functions in terms of simple macro language symbols which can be defined in an extended language L/sub k//sup +/; and 2) the construction of recursive systems of simple macro actions to express complex control actions.
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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) | 0.000 | 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".