Collective activity and autonomous characters: trust-based decision-making system

Collective activity and autonomous characters: trust-based decision-making system

Lucile Callebert Domitile Lourdeaux Jean-Paul Barthès 

Sorbonne universités, Université de technologie de Compiègne, CNRS, Heudiasyc UMR 7253, CS 60 319, 60 203 Compiègne, France

Corresponding Author Email: 
lucile.callebert@hds.utc.fr; domitile.lourdeaux@hds.utc.fr; jean-paul.barthes@hds.utc.fr
Page: 
153-181
|
DOI: 
https://doi.org/10.3166/RIA.31.153-181
Received: 
| |
Accepted: 
| | Citation

OPEN ACCESS

Abstract: 

When working in teams, people make mistakes. To train someone in a collaborative virtual environment to adapt to teammates that bahave non optimally, we propose (1) an augmentation of the ACTIVITY-Description Language as well as mechanisms of propagation of constraints that will facilitate agents’ reasoning; and (2) an agent model in which each agent is described through three dimensions (integrity, benevolence, abilities) corresponding to the MDS trust model. Besides each agent has different personal and collective goals and has beliefs about others’ integrity, benevolence and abilities. This agent model is associated to a decision-making system that allows agents to adopt human-like behaviors. In particular, agents take others into account and are able to reason on their beliefs about others both when choosing which goal (collective or individual) to focus on and when selecting a task. We conducted a preliminary evaluation in which participants evaluated the behaviors produced with our system.

Keywords: 

multi-agents systems, decision-making, trust, collective activity

1. Introduction
2. Fondements théoriques
3. Travaux connexes
4. Description et traitement de l’activité collective
5. Moteur décisionnel
6. Évaluation préliminaire
7. Conclusion et perspectives
Remerciements

Ces travaux ont été menés dans le cadre d'une thèse financée par la Direction Générale de l'Armement (DGA) et le Labex MS2T, lui-même financé par le gouvernement français au travers du programme Investissements d’avenir géré par l'Agence Nationale de la Recherche (ANR – référence ANR-11-IDEX-0004-02).

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