Toward an Integrated Approach to Perception and Action: Conference Report and Future Directions
Bibliographic record
Abstract
This article was motivated by the conference entitled "Perception & Action - An Interdisciplinary Approach to Cognitive Systems Theory," which took place September 14-16, 2010 at the Santa Fe Institute, NM, USA. The goal of the conference was to bring together an interdisciplinary group of neuroscientists, roboticists, and theorists to discuss the extent and implications of action-perception integration in the brain. The motivation for the conference was the realization that it is a widespread approach in biological, theoretical, and computational neuroscience to investigate sensory and motor function of the brain in isolation from one another, while at the same time, it is generally appreciated that sensory and motor processing cannot be fully separated. Our article summarizes the key findings of the conference, provides a hypothetical model that integrates the major themes and concepts presented at the conference, and concludes with a perspective on future challenges in the field.
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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 | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".