Extreme Sensitive Robotic - A Context-Aware Ubiquitous Learning

Nicolas Verstaevel, Christine Régis, Valérian Guivarch, Marie-Pierre Gleizes, Fabrice Robert

2015

Abstract

Our work focuses on Extreme Sensitive Robotic that is on multi-robot applications that are in strong interaction with humans and their integration in a highly connected world. Because human-robots interactions have to be as natural as possible, we propose an approach where robots Learn from Demonstrations, memorize contexts of learning and self-organize their parts to adapt themselves to new contexts. To deal with Extreme Sensitive Robotic, we propose to use both an Adaptive Multi-Agent System (AMAS) approach and a Context-Learning pattern in order to build a multi-agent system ALEX (Adaptive Learner by Experiments) for contextual learning from demonstrations.

Paper Citation

in Harvard Style

Verstaevel N., Régis C., Guivarch V., Gleizes M. and Robert F. (2015). Extreme Sensitive Robotic - A Context-Aware Ubiquitous Learning . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-073-4, pages 242-248. DOI: 10.5220/0005282002420248

in Bibtex Style

@conference{icaart15,
author={Nicolas Verstaevel and Christine Régis and Valérian Guivarch and Marie-Pierre Gleizes and Fabrice Robert},
title={Extreme Sensitive Robotic - A Context-Aware Ubiquitous Learning},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2015},
pages={242-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005282002420248},
isbn={978-989-758-073-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Extreme Sensitive Robotic - A Context-Aware Ubiquitous Learning
SN - 978-989-758-073-4
AU - Verstaevel N.
AU - Régis C.
AU - Guivarch V.
AU - Gleizes M.
AU - Robert F.
PY - 2015
SP - 242
EP - 248
DO - 10.5220/0005282002420248