Toward State Space Island Identification in Multi-process Bidirectional Heuristic Search
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-process bidirectional heuristic search algorithms that utilize island nodes (such as PBA*) have been shown to have the potential for exponential speedup over their plain counterparts that do not utilize island nodes. However, the performance of the former can dramatically degrade if the island nodes are not appropriately placed in the state space prior to the beginning of such algorithms. The problem of how to generate appropriately located island nodes has resisted any general purpose solution to date. This work is an initial proposal toward this end. We implement our method and evaluate its performance within PBA* for a variety of sliding-tiles puzzles. Our findings reveal that the overhead cost of using our method is negligible, while at the same time, when PBA* is equipped with the proposed method, it outperforms its random-island-nodes counterpart by over 80% of the time.
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) | 0.000 | 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