How search images limit competition: The role of attention in collective foraging.
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
Many species forage collectively, and this will shape how they search for prey. However, theories of visual attention and search image formation have not considered social foraging, and studies of collective foraging rarely consider cognitive constraints. Here, we connected these ideas and present an agent-based model of collective foraging on cryptic prey in agents that either can or cannot form search images. Agents focused on one prey type reduce its local density, biasing other agents to form search images for other prey types. This effect, attentional character displacement, may reduce competition, as foragers occupy separate regions of "attention-space." We found that the ability to modulate attention increases distance in attention-space and reduces competition, improving success rates. Agents that cannot modulate their attention benefit from foraging with those that can. We also found that some top-down control of search is critical to taking advantage of this effect. This cognitive-ecological approach to modeling collective foraging suggests that competition is a critical driver of the evolution of search images. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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