Robustness in evolved grid structures
Bibliographic record
Abstract
This study explores the ability of dynamic polyominos to acquire different types of robustness in a variety of environments. A polyomino is a collection of identical squares joined along their sides to form a connected shape. This study introduces a cellular encoding for polyominos that grow in a manner that adapts to environmental obstructions. Fitness evaluation places polyominos in competition to occupy space with each square of a grid occupiable by only a single individual. Evolved polyomino genomes are studied for their robustness to choice of opponent and environment. This study is part of a series studying the evolution of robustness, enlarging the scope of the series to include robustness against choice of opponent and environment. Polyomino fitness is evaluated in monoculture, multiculture, and obstructed environments. It is found that in all cases added time evolving grants a greater degree of robustness than the other possible sources of robustness. When polyomino genomes have been evolved for comparable amounts of time it is found those with competitive fitness evaluation are superior. When the impact of environmental obstructions are considered it is found that being in your home environment grants a competitive advantage, though not as strong of an advantage as added evolution, with a single exception.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".