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Self-adaptation of a learnt behaviour by detecting and by managing user's implicit contradictions

Guivarch, Valérian and Camps, Valérie and Péninou, André and Glize, Pierre Self-adaptation of a learnt behaviour by detecting and by managing user's implicit contradictions. (2014) In: IEEE/WIC/ACM International Conference on Intelligent Agent Technology - IAT 2014, 11 August 2014 - 14 August 2014 (Warsaw, Poland).

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Official URL: http://dx.doi.org/10.1109/WI-IAT.2014.146

Abstract

This paper tackles the issue of ambient systems adaptation to users' needs while the environment and users' preferences evolve continuously. We propose the adaptive multi-agent system Amadeus whose goal is to learn from users' actions and contexts how to perform actions on behalf of the users in similar contexts. However, considering the possible changes of users preferences, a previously learnt behaviour may become misfit. So, Amadeus must be able to observe if its actions on the system are contradicted by the users or not, without requiring any explicit feedback. The aim of this paper is to present the introspection capabilities of Amadeus in order to detect users contradictions and to self-adapt its behaviour at runtime. These mechanisms are then evaluated through a case study.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6928164
HAL Id:hal-01147253
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:24 Mar 2015 14:53

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