A Mobile Agent System for University Course Timetabling.
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
Abstract. A mobile multi-agent system is proposed to create solutions for the university course timetabling problem. It is composed of four kinds of agents: (mobile) Course Agents, and (stationary) Signboard, Publisher and Interface Agents. The key strength of this new approach is to use a fundamental attribute of Agents that of autonomy. This autonomy is manifested in this work in the Course Agent. Each Course Agent in the system is responsible for negotiating with other Course Agents to find satisfactory class resource for the course they represent. This negotiation occurs initially indirectly through a Signboard Agent. A set of rules is used to structure Agent-to-Agent negotiation to find mutually acceptable class resources. The scheduling problem is executed in a natural parallel structure using one Signboard Agent to represent a weekday. The experimental results show that this new approach has merit and can lead to acceptable and flexible solutions to the course timetabling problem. 1
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 | 0.000 | 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 | 0.001 | 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