Computational human-robot interaction
We present a systematic survey of computational research in humanrobot interaction (HRI)
over the past decade. Computational HRI is the subset of the field that is specifically …
over the past decade. Computational HRI is the subset of the field that is specifically …
[PDF][PDF] Learning from demonstration (programming by demonstration)
S Calinon - Encyclopedia of robotics, 2018 - idiap.ch
Learning from demonstration (LfD), also called Programming by demonstration (PbD), refers
to the process used to transfer new skills to a machine by relying on demonstrations from a …
to the process used to transfer new skills to a machine by relying on demonstrations from a …
The effects of a robot's performance on human teachers for learning from demonstration tasks
Learning from Demonstration (LfD) algorithms seek to enable end-users to teach robots new
skills through human demonstration of a task. Previous studies have analyzed how robot …
skills through human demonstration of a task. Previous studies have analyzed how robot …
Why robots should be social: Enhancing machine learning through social human-robot interaction
Social learning is a powerful method for cultural propagation of knowledge and skills relying
on a complex interplay of learning strategies, social ecology and the human propensity for …
on a complex interplay of learning strategies, social ecology and the human propensity for …
Towards grounding concepts for transfer in goal learning from demonstration
We aim to build robots that frame the task learning problem as goal inference so that they
are natural to teach and meet people's expectations for a learning partner. The focus of this …
are natural to teach and meet people's expectations for a learning partner. The focus of this …
Discovering task constraints through observation and active learning
Effective robot collaborators that work with humans require an understanding of the
underlying constraint network of any joint task to be performed. Discovering this network …
underlying constraint network of any joint task to be performed. Discovering this network …
Machine learning for interactive systems and robots: a brief introduction
Research on interactive systems and robots, ie interactive machines that perceive, act and
communicate, has applied a multitude of different machine learning frameworks in recent …
communicate, has applied a multitude of different machine learning frameworks in recent …
Interactive teaching and experience extraction for learning about objects and robot activities
Intelligent service robots should be able to improve their knowledge from accumulated
experiences through continuous interaction with the environment, and in particular with …
experiences through continuous interaction with the environment, and in particular with …
Augmented reinforcement learning for interaction with non-expert humans in agent domains
M Sridharan - 2011 10th International Conference on Machine …, 2011 - ieeexplore.ieee.org
In application domains characterized by dynamic changes and non-deterministic action
outcomes, it is frequently difficult for agents or robots to operate without any human …
outcomes, it is frequently difficult for agents or robots to operate without any human …
A taxonomy for characterizing modes of interactions in goal-driven, human-robot teams
As robots and other autonomous agents are increasingly incorporated into complex
domains, characterizing interaction within heterogeneous teams that include both humans …
domains, characterizing interaction within heterogeneous teams that include both humans …