Optimization and Performance Analysis of Fractional Order PID Controller for DC Motor Speed Control
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
Multi-Agent System (MAS) technology is one of the cores and promising areas in the field of Artificial Intelligence (AI) as well as in the stream of Computer Science. The technology is comprised of multiple decision-making agents that exist in an environment to achieve common or conflicting goals. Multi-Agent System technology has a rapid growth and evolution due to its marvelous features such as flexibility and intelligence that are very useful when solving complex distributed problems. This paper focuses on the history and evolution of MAS technology, present applications, and future trends by addressing more detailed explanations about the foundations or key principles of Multi-Agent System technology such as agents, agent taxonomy, agent communication approaches, MAS development frameworks as well as the history of agent technology. The goal of this paper is to provide broad and comprehensive knowledge about Multi-Agents System technology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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