How can I find what I want? Can children, chimpanzees and capuchin monkeys form abstract representations to guide their behavior in a sampling task?
Bibliographic record
Abstract
concepts are a powerful tool for making wide-ranging predictions in new situations based on little experience. Whereas looking-time studies suggest an early emergence of this ability in human infancy, other paradigms like the relational match to sample task often fail to detect abstract concepts until late preschool years. Similarly, non-human animals show difficulties and often succeed only after long training regimes. Given the considerable influence of slight task modifications, the conclusiveness of these findings for the development and phylogenetic distribution of abstract reasoning is debated. Here, we tested the abilities of 3 to 5-year-old children, chimpanzees, and capuchin monkeys in a unified and more ecologically valid task design based on the concept of "overhypotheses" (Goodman, 1955). Participants sampled high- and low-valued items from containers that either each offered items of uniform value or a mix of high- and low-valued items. In a test situation, participants should switch away earlier from a container offering low-valued items when they learned that, in general, items within a container are of the same type, but should stay longer if they formed the overhypothesis that containers bear a mix of types. We compared each species' performance to the predictions of a probabilistic hierarchical Bayesian model forming overhypotheses at a first and second level of abstraction, adapted to each species' reward preferences. Children and, to a more limited extent, chimpanzees demonstrated their sensitivity to abstract patterns in the evidence. In contrast, capuchin monkeys did not exhibit conclusive evidence for the ability of abstract knowledge formation.
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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 | 0.000 | 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 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".