The DOI matches its Crossref record; 87 of the 87 references it cites were found in a registry or an index.
Is imitation learning the route to humanoid robots?
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Citations
Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
Reinforcement Learning: An Introduction
(2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 24,496
Neural networks for pattern recognition
(1994) · Choice Reviews Online · doi:10.5860/choice.31-5500 · Cited by 18,538
Reinforcement Learning: A Survey
Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996) · Journal of Artificial Intelligence Research · doi:10.1613/jair.301 · Cited by 8,972
Play, Dreams And Imitation In Childhood
Piaget, J. (2013) · Routledge eBooks · doi:10.4324/9781315009698 · Cited by 5,360
Learning to predict by the methods of temporal differences
Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148
Premotor cortex and the recognition of motor actions
Rizzolatti, G., Fadiga, L., Gallese, V., & Fogassi, L. (1996) · Cognitive Brain Research · doi:10.1016/0926-6410(95)00038-0 · Cited by 4,870
Understanding motor events: a neurophysiological study
di Pellegrino, G., Fadiga, L., Fogassi, L., Gallese, V., & Rizzolatti, G. (1992) · Experimental Brain Research · doi:10.1007/bf00230027 · Cited by 3,539
Imitation of Facial and Manual Gestures by Human Neonates
Meltzoff, A. N., & Moore, M. K. (1977) · Science · doi:10.1126/science.198.4312.75 · Cited by 3,263
Mirror neurons and the simulation theory of mind-reading
Gallese, V (1998) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(98)01262-5 · Cited by 3,201
Cited by
Reinforcement learning in robotics: A survey
Kober, J., Bagnell, J. A., & Peters, J. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913495721 · Cited by 3,160
Imitation Learning: A Survey of Learning Methods
Hussein, A., Gaber, M. M., Elyan, E., & Jayne, C. (2018) · ACM Computing Surveys · doi:10.1145/3054912 · Cited by 1,060
Deep Reinforcement Learning: A Survey
Wang, X., Wang, S., Liang, X., Zhao, D., Huang, J., Xu, X., Dai, B., & Miao, Q. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3207346 · Cited by 972
Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models
Khansari-Zadeh, S. M., & Billard, A. (2011) · IEEE Transactions on Robotics · doi:10.1109/tro.2011.2159412 · Cited by 771
Foundations for a new science of learning
Meltzoff, A. N., Kuhl, P. K., Movellan, J., & Sejnowski, T. J. (2009) · Science · doi:10.1126/science.1175626 · Cited by 723
Metadata
- Authors
- Schaal, S.
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 1999-06
- Volume
- 3
- Issue
- 6
- Pages
- 233-242
- ISSN
- 1364-6613 (ISSN-L)
- OpenAlex
- W2166302491
- Cited by
- 1,314
- References
- 87
- FWCI
- 7.49
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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- CoChat. (2026). Citation check: Is imitation learning the route to humanoid robots? https://app.cochat.ai/papers/10.1016/s1364-6613(99)01327-3
- The paper
- Schaal, S. (1999). Is imitation learning the route to humanoid robots? Trends in Cognitive Sciences. https://doi.org/10.1016/s1364-6613(99)01327-3
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.
