loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Nicolas Verstaevel 1 ; Christine Régis 2 ; Valérian Guivarch 2 ; Marie-Pierre Gleizes 2 and Fabrice Robert 3

Affiliations: 1 Université Paul Sabatier and Sogeti High Tech, France ; 2 Université Paul Sabatier, France ; 3 Sogeti High Tech, France

ISBN: 978-989-758-073-4

Keyword(s): Ambient Intelligence, Self-Organizing Systems, Machine Learning, Adaptive Multi-Agent Systems, Robot and Multi-Robot Systems.

Related Ontology Subjects/Areas/Topics: Agents ; Ambient Intelligence ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Machine Learning ; Multi-Agent Systems ; Robot and Multi-Robot Systems ; Self Organizing Systems ; Soft Computing ; Software Engineering ; Symbolic Systems

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.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.91.106.44

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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 2: ICAART, ISBN 978-989-758-073-4, pages 242-248. DOI: 10.5220/0005282002420248

@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 2: ICAART,},
year={2015},
pages={242-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005282002420248},
isbn={978-989-758-073-4},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: 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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.