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Knowledge- and ambiguity-aware robot learning from corrective and evaluative feedback
In order to deploy robots that could be adapted by non-expert users, interactive imitation learning (IIL) methods must be flexible regarding the interaction preferences of the teacher and avoid assumptions of perfect teachers (oracles), while considering they make mistakes influenced by diverse huma...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer London
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338625/ https://www.ncbi.nlm.nih.gov/pubmed/37455835 http://dx.doi.org/10.1007/s00521-022-08118-z |