Non-deterministic planning methods for automated web service composition
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
Web service composition (WSC) is the task of generating new composite web services that exhibit functionalities not supported by any single web service. In its simplest form this is achieved by linking existing web services in sequence. More complex forms link services in parallel or use alternative paths. WSC can be considered a planning task, with the web services being the planning operators and the initial state and the goals being provided by the user. Particularly, since web services operate in a stochastic environment, their output is not predictable, and the problem is formulated as a non-deterministic planning one. This article presents a critical, comprehensive and up-to-date review of the literature concerning alternative non-deterministic planning methods, including probabilistic planning, determinization methods, planning in the belief state space and translation based methods. Furthermore, the article reviews existing implementations of WSC systems, employing a variety of planning approaches, and discusses the degree in which the current achievements from the non-deterministic planning field have been adopted successfully. To the best of our knowledge, this is the first review of its kind, one that provides a thorough introduction to the vast area of automated web service composition.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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