Rapid Application Development Using Agent Itinerary Patterns
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
. The behavior of mobile agents is often prescribed by a set of tasks represented in an itinerary. We have used a variety of agent itinerary styles, ranging from simple, sequential expressions to complex, finite state-based representations. The design and implementation of an itinerary can be a complex, time intensive task, particularly in mobile agent architectures, where resources and task execution occur in a distributed network. To address this issue, we have developed a set of reusable, flexible itinerary patterns that enable the rapid development of complex agent itineraries. Used in conjunction with a task library, these itinerary patterns have reduced our time to develop agent applications by up to 40 percent. 1 Introduction Itineraries are frequently used as a control structure in mobile agent systems, because some sort of checkpointing or discrete separation among tasks is useful in supporting weak mobility. Moreover, mobile agents perform tasks at locations, and i...
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.036 | 0.001 |
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