Learning from Humans

222 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

An Incremental Self-Organizing Architecture for Sensorimotor Learning and Prediction (2017, background): “This topic has been the focus of a number of studies on programming by demonstration [28].”
Imitation Learning as f-Divergence Minimization (2019, background): “[5] Aude G Billard, Sylvain Calinon, and Rüdiger Dillmann.”
Recent Advances in Robot Learning from Demonstration (2020, background): “(2, 10) presented broad syntheses of LfD that incorporated elements of human–robot interaction and framed the inquiry from the perspective of four core questions for the field: how, what, when, and whom to imitate.”
Boosted Curriculum Reinforcement Learning (2022, unknown): “…various forms, e.g., via samples (Lazaric et al., 2008; Lazaric & Restelli, 2011), policies (Fern´andez & Veloso, 2006; Fern´andez et al., 2010; Silver et al., 2018), reward functions (Brys et al., 2015) or demonstrations/teachers (Chernova & Veloso, 2009; Billard et al., 2016; Koert et al., 2020).”
Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications (2018, background): “Additionally, the use of collaborative robots in industrial processes proves beneficial also given the fact that they can be managed and taught through intuitive systems, based on augmented reality [5], walkthrough programming [6,7] or programming by demonstration [8], just to cite few examples.”