Zobrazeno 1 - 10
of 96
pro vyhledávání: '"J. Gentili"'
Autor:
V. Castro, S.S. Azevedo, T.B. Gotti, C.S.A. Batista, J. Gentili, Z.M. Morais, S.A. Vasconcellos, M.E. Genovez
Publikováno v:
Arquivo Brasileiro de Medicina Veterinária e Zootecnia, Vol 61, Iss 6, Pp 1438-1442 (2009)
Externí odkaz:
https://doaj.org/article/47d3aafd311642b6864117f1d00bc99b
Autor:
Alexandra A. Shaver, Calvin M. Lu, Christopher Gaskins, James A. Reggia, James Purtilo, Rodolphe J. Gentili
Publikováno v:
2023 11th International IEEE/EMBS Conference on Neural Engineering (NER).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::653b0583ebbecf16249c5807d51b56f9
https://doi.org/10.1109/ner52421.2023.10123908
https://doi.org/10.1109/ner52421.2023.10123908
Publikováno v:
2023 57th Annual Conference on Information Sciences and Systems (CISS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6859f3d4d1d2222dffebb9779a48a715
https://doi.org/10.1109/ciss56502.2023.10089662
https://doi.org/10.1109/ciss56502.2023.10089662
Imitation learning allows social robots to learn new skills from human teachers without substantial manual programming, but it is difficult for robotic imitation learning systems to generalize demonstrated skills as well as human learners do. Contemp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5be2c24799c9dac47910892fb2b716b
http://arxiv.org/abs/2211.06462
http://arxiv.org/abs/2211.06462
Publikováno v:
Neural Networks. 138:78-97
Compositionality refers to the ability of an intelligent system to construct models out of reusable parts. This is critical for the productivity and generalization of human reasoning, and is considered a necessary ingredient for human-level artificia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e27fac07a20f8b08955b0f3ee9ec1031
https://doi.org/10.1016/j.neunet.2021.01.031
https://doi.org/10.1016/j.neunet.2021.01.031
Autor:
C. Lu, Steven Kahl, Yingzhi Lu, Bradley M. Ritland, B. Hatfield, Kyle J. Jaquess, Rodolphe J. Gentili, A. Ginsberg
Publikováno v:
Journal of Motor Behavior. 53:632-643
Evidence has accumulated that learners participating in self-controlled practice can both acquire skills and process task-relevant information more effectively than those participating in externally controlled practice. However, the impact of self-co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c7778be7927b8e265e64bb068a766ba
https://doi.org/10.1080/00222895.2020.1817841
https://doi.org/10.1080/00222895.2020.1817841
Autor:
Theresa C. Hauge, Gregory P. Davis, James A. Reggia, Di-Wei Huang, Rodolphe J. Gentili, Garrett E. Katz
Publikováno v:
International Journal of Social Robotics. 13:981-998
Examining complex cognitive-motor performance in humanoid robots and humans can inform their interactions in a social context of team dynamics. Namely, the understanding of human cognitive-motor control and learning mechanisms can inform human motor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94ecbe259136b36217fdad3d98d13e75
https://doi.org/10.1007/s12369-020-00685-2
https://doi.org/10.1007/s12369-020-00685-2
Autor:
Alexandra A. Shaver, Neehar Peri, Remy Mezebish, George Matthew, Alyza Berson, Christopher Gaskins, Gregory P. Davis, Garrett E. Katz, Immanuel Samuel, Matthew J. Reinhard, Michelle E. Costanzo, James A. Reggia, James Purtilo, Rodolphe J. Gentili
Publikováno v:
Augmented Cognition ISBN: 9783031054563
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c00c348f3a44f7b0e010c3800d79768
https://doi.org/10.1007/978-3-031-05457-0_28
https://doi.org/10.1007/978-3-031-05457-0_28
Autor:
Patricia A. Shewokis, Emma P. Shaw, Isabelle M. Shuggi, Maria J. Ayoub, Helena Wu, Hyuk Oh, Rodolphe J. Gentili, Arianna Moreno
Publikováno v:
Neuroscience. 423:232-248
The human capability to learn new motor skills depends on the efficient engagement of cognitive-motor resources, as reflected by mental workload, and psychological mechanisms (e.g., self-efficacy). While numerous investigations have examined the rela
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b27ff3a60fa97321cff45ff3dff81a32
https://doi.org/10.1016/j.neuroscience.2019.07.001
https://doi.org/10.1016/j.neuroscience.2019.07.001
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 146
Despite significant improvements in contemporary machine learning, symbolic methods currently outperform artificial neural networks on tasks that involve compositional reasoning, such as goal-directed planning and logical inference. This illustrates
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7c72524ef46ba7238c7808351d622bf
https://pubmed.ncbi.nlm.nih.gov/34894482
https://pubmed.ncbi.nlm.nih.gov/34894482