A Complex Adaptive System of Systems Approach to Human–Automation Interaction in Smart Grid
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This chapter expresses three cognitive genres: descriptive genre, normative/prescriptive genre, and know-how genre. The descriptive genre introduces and discusses on the following disciplines: the core concepts of complexity, complex adaptive system (CAS) of systems (CASoS), the application domains of human-automation interaction (HAI) and adaptive autonomy (AA), especially in Smart Grid, and two implementation ideas of expert systems and Petri nets. The chapter describes the automation related notions, that is, automation and HAI, followed by the investigation of HAI models' evolution from the perspectives of dimensions and dynamism. The idea of AA is then introduced as a dynamic HAI scheme, followed by the classification of AA implementation methods. Petri nets are introduced as powerful tools for modeling complex systems (CxS). Finally, Petri net realization of the adaptive autonomy expert system (AAES) is presented, followed by a performance evaluation study.
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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 | 0.001 | 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