Map Abstraction with Adjustable Time Bounds
Bibliographic record
Abstract
The paper presented here addresses the problem of path planning in real time strategy games. We have proposed a new algorithm titled Map Abstraction with Adjustable Time Bounds. This algorithm uses an abstract map containing non-uniformly sized triangular sectors; the centroids of the sectors guide the path search in the game map. In a pre-processing step we calculate an upper and lower time limit to plan paths for a given two dimensional grid map that is known beforehand. Depending on the time limits, we vary the size of the sectors to save search time or to improve path quality. We have experimented using maps from commercial games such as Dragon’s Age: Origins and Warcraft III. In the worst case MAAT returns paths that are 8% less optimal. MAAT has an expensive pre-processing step which ultimately lowers the overhead CPU time consumed during game play by 1.1 milliseconds.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.014 |
| Open science | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".