Landmark navigation in a virtual environment: Integrative contributions from global and local landmarks
Bibliographic record
Abstract
Previous experiments have shown that human beings and other animals can find their way to a familiar location using combinations of both local and global landmarks. Several studies, particularly those using non-humans, have suggested that global landmarks take precedence over local landmarks. Other experiments have suggested that a combination of sources of location information are used, weighted by the exigencies of a particular trial. In the present experiment, we examined the ability of people to navigate to locations in a virtual environment using combinations of local and global landmarks. The virtual environment was generated using a large screen and look-through stereoscopic glasses with motion tracking. The environment consisted of a 91.4 metre diameter round field containing an array of six simple geometric solids. The background consisted of a panoramic display of a suburban park. On learning trials, participants were required to navigate to the target using a handheld device and to touch the target with a virtual wand. On the immediately following test trial, the display reset, the target was extinguished and participants were displaced to a new location on the field. They were then required to navigate back to the original location of the target and to touch the ground with the wand. On some trials, the local landmarks were displaced by either 30 or 60 degrees before the test trial. Results suggested that although there was a small influence of local landmark shifts, participants relied primarily on global landmarks in this experiment. In addition, there was some tendency for searches on shift trials to take longer and to be more circuitous. In accord with previous research, we found strong trial effects and individual differences, suggesting that no uniform strategy was adopted. In debriefing, participants reported a variety of different strategies, but there was little or no correlation between these reports and the behavioural evidence.
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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".