The DOI matches its Crossref record; 176 of the 176 references it cites were found in a registry or an index.
Cognitive Developmental Robotics: A Survey
Abstract
Cognitive developmental robotics (CDR) aims to provide new understanding of how human's higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions. The core idea of CDR is ldquophysical embodimentrdquo that enables information structuring through interactions with the environment, including other agents. The idea is shaped based on the hypothesized development model of human cognitive functions from body representation to social behavior. Along with the model, studies of CDR and related works are introduced, and discussion on the model and future issues are argued.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388
The attention system of the human brain
Posner, M. I., & Petersen, S. E. (1990) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.13.030190.000325 · Cited by 8,070 · cited 2×
“The brain region active for responding to joint attention is the same as the region of general attention (the left parietal lobe), but that for the ability to initiate joint attention includes the prefrontal area and close to the area for language [21], [22].”
BackgroundStatistical learning by 8-month-old infants
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996) · Science · doi:10.1126/science.274.5294.1926 · Cited by 5,659
Buzsáki, G. (2006) · doi:10.1093/acprof:oso/9780195301069.001.0001 · Cited by 4,873
Intelligence without representation
Brooks, R. A. (1991) · Artificial Intelligence · doi:10.1016/0004-3702(91)90053-m · Cited by 4,853
The Construction Of Reality In The Child
Piaget, J. (2013) · Routledge eBooks · doi:10.4324/9781315009650 · Cited by 4,568
The construction of reality in the child.
Piaget, J. (1954) · doi:10.1037/11168-000 · Cited by 4,558
Measuring Information Transfer
Schreiber, T. (2000) · Physical Review Letters · doi:10.1103/physrevlett.85.461 · Cited by 4,530
Empathy for Pain Involves the Affective but not Sensory Components of Pain
Singer, T., Seymour, B., O'Doherty, J., Kaube, H., Dolan, R. J., & Frith, C. D. (2004) · Science · doi:10.1126/science.1093535 · Cited by 3,929
Meeting of minds: the medial frontal cortex and social cognition
Amodio, D. M., & Frith, C. D. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn1884 · Cited by 3,782 · cited 3×
“ferent brain regions were activated under each condition: medial prefrontal cortex [47] in CUP; left anterior intraparietal sulcus [122] in GRASP; bilateral superior parietal lobes [123] in HAND; and left premotor and primary motor areas [124] in PATH.”
Background
Cited by
Information-seeking, curiosity, and attention: computational and neural mechanisms
Gottlieb, J., Oudeyer, P.-Y., Lopes, M., & Baranes, A. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.09.001 · Cited by 784
Empathy in Virtual Agents and Robots: A Survey
Paiva, A., Leite, I., Boukricha, H., & Wachsmuth, I. (2017) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/2912150 · Cited by 361
On the Measure of Intelligence
Chollet, F. (2019) · arXiv · doi:10.48550/arxiv.1911.01547 · Cited by 218
Symbol emergence in robotics: a survey
Taniguchi, T., Nagai, T., Nakamura, T., Iwahashi, N., Ogata, T., & Asoh, H. (2016) · Advanced Robotics · doi:10.1080/01691864.2016.1164622 · Cited by 150
Cognition from the bottom up: on biological inspiration, body morphology, and soft materials
Pfeifer, R., Iida, F., & Lungarella, M. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.04.004 · Cited by 120
Metadata
- Authors
- Asada, M., Hosoda, K., Kuniyoshi, Y., Ishiguro, H., Inui, T., Yoshikawa, Y., Ogino, M., & Yoshida, C.
- Venue
- IEEE Transactions on Autonomous Mental Development
- Published
- 2009-05
- Volume
- 1
- Issue
- 1
- Pages
- 12-34
- ISSN
- 1943-0604 (ISSN-L)
- 1943-0612
- OpenAlex
- W2155352776
- Cited by
- 554
- References
- 176
- FWCI
- 50.56
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Cognitive Developmental Robotics: A Survey. https://app.cochat.ai/papers/10.1109/tamd.2009.2021702
- The paper
- Asada, M., Hosoda, K., Kuniyoshi, Y., Ishiguro, H., Inui, T., Yoshikawa, Y., Ogino, M., & Yoshida, C. (2009). Cognitive Developmental Robotics: A Survey. IEEE Transactions on Autonomous Mental Development. https://doi.org/10.1109/tamd.2009.2021702
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.