@inproceedings{7271bc40d71442de801ec95d6c30bddb,
title = "Teaching robots by moulding behavior and scaffolding the environment",
abstract = "Programming robots to carry out useful tasks is both a complex and non-trivial exercise. A simple and intuitive method to allow humans to train and shape robot behaviour is clearly a key goal in making this task easier. This paper describes an approach to this problem based on studies of social animals where two teaching strategies are applied to allow a human teacher to train a robot by moulding its actions within a carefully scaffolded environment. Within these enviroments sets of competences can be built by building state/action memory maps of the robot's interaction within that environment. These memory maps are then polled using a k-nearest neighbour based algorithm to provide a generalised competence. We take a novel approach in building the memory models by allowing the human teacher to construct them in a hierarchical manner. This mechanism allows a human trainer to build and extend an action-selection mechanism into which new skills can be added to the robot's repertoire of existing competencies. These techniques are implemented on physical Khepera miniature robots and validated on a variety of tasks.",
keywords = "Imitation, Memory-based learning, Scaffolding, Social Robotics, Teaching, Zone of Proximal Development",
author = "Joe Saunders and Nehaniv, {Chrystopher L.} and Kerstin Dautenhahn",
year = "2006",
month = jul,
day = "17",
language = "English",
isbn = "1595932941",
series = "HRI 2006: Proceedings of the 2006 ACM Conference on Human-Robot Interaction",
pages = "118--125",
booktitle = "HRI 2006",
note = "HRI 2006: 2006 ACM Conference on Human-Robot Interaction ; Conference date: 02-03-2006 Through 04-03-2006",
}