About cooperation of multiagent teams: A model to use collective products

About cooperation of multiagent teams: A model to use collective products

Afra Khenifar-Bessadi Jean-Paul Jamont Michel Occello Choukri-Bey Ben-Yelles Mouloud Koudil 

LMCS, École Nationale Supérieure d'Informatique, 16309-Alger, Algérie

Univ. Grenoble Alpes, LCIS, F-26000 Valence, France

Corresponding Author Email: 
a_khenifar@esi.dz; m_koudil@esi.dz; jean-paul.jamont@lcis.grenoble-inp.fr; michel.occello@lcis.grenoble-inp.fr; choukri.ben-yelles@lcis.grenoble-inp.fr
Page: 
97-132
|
DOI: 
https://doi.org/10.3166/RIA.31.97-132
Received: 
|
Accepted: 
|
Published: 
30 April 2017
| Citation
Abstract: 

A multiagent system is a set of agents which collaborate and realize a collective product. We are interested by teams where agents have only a partial view on their team and of the collective products they generate. Teams cooperation allows them to exploit each other collective products, instead of exploiting individually the skills of agents from each team. This cooperation can help each team to realize or to enhance its own products. We propose a model to allow the cooperation of distributed preexisting teams by avoiding the disturbance of the initial functioning of each team. To meet this constraint, we insert virtual probes into each team to observe and to influence the agents in order to allow their cooperation by using collective products. The proposed approach is evaluated on a scenario where a sensor network and a drone network need to cooperate while designed and deployed separately.

Keywords: 

collective product, inter-MAS Cooperation, multi-agent systems

1. Introduction
2. Coopération de collectifs
3. Une approche pour la coopération de collectifs
4. Opérationnalisation de la coopération des collectifs
5. Application
6. Discussion
7. Conclusion et perspectives
  References

Adam E., Mandiau R., Kolski C. (2001). Application of a holonic multi-agent system for cooperative work to administrative processes. Journal of Applied Systems, vol. 2, no 1, p. 100-115.

Adam E., Mandiau R., Kolski C. (2002). Une méthode de modelisation et de conception d'organizations multi-agents holoniques. In Organisation et applications des sma, p. 41-75. Hermes, Paris.

Archimède B., Memon M. A., Ishak K. (2016). Combining multi-agent model, soa and ontologies in a distributed and interoperable architecture to manage multi-site production projects. International Journal of Computer Integrated Manufacturing, p. 1–15.

Atlan H. (2000). La finalité. Hors série Sciences et Avenir, vol. 47.

Buccafurri F., Rosaci D., Sarnè G. M., Palopoli L. (2004). Modeling cooperation in multi-agent communities. Cognitive Systems Research, vol. 5, no 3, p. 171-190.

Castelfranchi C. (1998). Modelling social action for ai agents. Artificial Intelligence, vol. 103, no 1, p. 157-182.

Cockburn D., Jennings N. R. (1996). Archon: A distributed artificial intelligence system for industrial applications. Foundations of Distributed Artificial Intelligence, p. 319–344.

Coutinho L. R., Brandão A., Sichman J. S., Hübner J. F., Boissier O. (2009). A model-based architecture for organizational interoperability in open multiagent systems. In International

workshop on coordination, organizations, institutions and norms in agent systems V, COIN 2009, p. 102–113.

David D., Courdier R. (2009). See emergence as a metaknowledge-a way to reify emergent phenomena in multiagent simulations? In ICAART 2009 - proceedings of the international conference on agents and artificial intelligence, p. 564-569. Porto, Portugal.

Fok C.-L., Roman G.-C., Lu C. (2005). Mobile agent middleware for sensor networks: An application case study. In Ipsn 2005. fourth international symposium on information processing in sensor networks, p. 382–387.

Fok C.-L., Roman G.-C., Lu C. (2009). Agilla: A mobile agent middleware for self-adaptive wireless sensor networks. ACM Transactions on Autonomous and Adaptive Systems (TAAS), vol. 4, no 3, p. 16.

Gaertner D., Rodríguez-Aguilar J. A., Toni F. (2008). Agreeing on institutional goals for multiagent societies. In International workshops on coordination, organizations, institutions and norms in agent systems IV, COIN 2008, p. 1–16. Chicago, USA.

Gascueña J. M., Garijo F. J., Fernández-Caballero A., Gleizes M. P., Glize P. (2012). Implementation and assessment of robot team cooperation models using deliberative control components. In Advances in artificial intelligence - IBERAMIA 2012 - proceedings of the 13th ibero-american conference on ai, p. 412–421. Cartagena de Indias, Colombia.

Georgé J.-P. (2004). Résolution de problèmes par émergence - étude d’un environnement de programmation émergente. Thèse de doctorat non publiée, Université de Toulouse III.

Goldstein J. (1999). Emergence as a construct: History and issues. Emergence, vol. 1, no 1, p. 49–72.

Halloy J., Sempo G., Caprari G., Rivault C., Asadpour M., Tâche F. et al. (2007). Social integration of robots into groups of cockroaches to control self-organized choices. Science, vol. 318, no 5853, p. 1155–1158.

Hoang T. T. H., Occello M., Jamont J.-P., Ben-Yelles C. (2012). Supervision de systèmes complexes artificiels décentralisés. proposition d’un modèle multi-agent récursif générique. Revue d’Intelligence Artificielle, vol. 26, no 5, p. 569–600.

Holland J. H. (2000). Emergence: From chaos to order. Oxford Univ Press.

Hsieh F.-S., Lin J.-B. (2016). A self-adaptation scheme for workflow management in multiagent systems. Journal of Intelligent Manufacturing, vol. 27, no 1, p. 131–148.

Jamont J.-P., Occello M., Lagrèze A. (2010). A multiagent approach to manage communication in wireless instrumentation systems. Measurement, vol. 43, no 4, p. 489-503.

Jamont J.-P., Occello M., Mendes E. (2013). Decentralized intelligent real world embedded systems: a tool to tune design and deployment. In Advances on practical applications of agents and multi-agent systems, 11th international conference, PAAMS 2013, salamanca, spain, may 22-24, 2013. proceedings, p. 133–144.

Khenifar A., Jamont J.-P., Occello M., Ben-Yelles C.-B., Koudil M. (2014). A recursive approach to enable the collective level interaction of the web of things applications. In Proceedings of international workshop on web intelligence and smart sensing, p. 1–2.

Khenifar-Bessadi A., Jamont J.-P., Occello M., Ben-Yelles C., Koudil M. (2016a). About cooperation of multiagent collective products: An approach in the context of cyber-physical systems. In Proceedings of IEEE RIVF international conference on computing & communication technologies, research, innovation, and vision for the future, p. 19–24.

Khenifar-Bessadi A., Jamont J.-P., Occello M., Ben-Yelles C., Koudil M. (2016b). De la coopération des productions collectives dans un contexte multi-agent. In Systèmes multi-agents et simulation - vingt-quatrièmes journées francophones sur les systèmes multi-agents, JFSMA 16, p. 43–52. Saint-Martin-du-Vivier (Rouen), France, Cépaduès Éditions.

Khenifar-Bessadi A., Jamont J.-P., Occello M., Koudil M. (2015). Vers une coopération des collectifs de systèmes multi-agents hétérogènes. In 13émes rencontres de jeunes chercheurs en intelligence artificielle, plate-forme intelligence artificielle,. Rennes, France.

Klein F., Bourjot C., Chevrier V. (2008). Contribution to the control of a mas’s global behaviour: Reinforcement learning tools. In Proceedings of the 9th international workshop engineering societies in the agents world, ESAW 2008, p. 173–190. Saint-Etienne, France.

Kozlowski S. W., Chao G. T., Grand J. A., Braun M. T., Kuljanin G. (2013). Advancing multilevel research design : capturing the dynamics of emergence. Organizational Research Methods, vol. 16, no 4, p. 581-615.

Kozlowski S. W., Klein K. J. (2000). A multilevel approach to theory and research in organizations: Contextual, temporal, and emergent processes. Multilevel theory, research and methods in organizations: Foundations, extensions, and new directions, p. 3–90.

Lamarche-Perrin R., Demazeau Y., Vincent J.-M. (2014). Building optimal macroscopic representations of complex multi-agent systems. In Transactions on computational collective intelligence xv, p. 1–27. Springer.

Lange S., Sünderhauf N., Protzel P. (2009). A vision based onboard approach for landing and position control of an autonomous multirotor uav in gps-denied environments. In Ieee international conference on advanced robotics, icar 2009, p. 1-6. IEEE.

Luciani A., Thil F., Evrard M. (2006). Mass-interaction model of emergent collective phenomena. In 10th international conference on computer animation and social agents, vol. 1, p. 197-206.

Mataric M. J. (1993). Designing emergent behaviors: From local interactions to collective intelligence. In proceedings of the second international conference on from animals to animats 2 : Simulation of adaptive behavior, p. 432–441. Cambridge, MA, USA, MIT Press.

Meron D., Mermet B. (2006). A tool architecture to verify properties of multiagent system at runtime. In International workshop on programming multi-agent systems, p. 201–216.

Müller J.-P. (2002). Des systèmes autonomes aux systèmes multi-agents: Interaction, émergenceet systèmes complexes. Thèse de doctorat non publiée, Université Libre de Bruxelles. 

Nardin L. G., Brandão A. A., Sichman J. S. (2011). Experiments on semantic interoperability of agent reputation models using the soari architecture. Engineering Applications of Artificial Intelligence, vol. 24, no. 8, p. 1461–1471.

O’Toole E., Nallur V., Clarke S. (2014). Towards decentralised detection of emergence in complex adaptive systems. In Eighth IEEE international conference on self-adaptive and self-organizing systems, p. 60–69.

Santos G., Pinto T., Vale Z., Praça I., Morais H. (2016). Enabling communications in heterogeneous multi-agent systems: Electricity markets ontology. Advances in Distributed Computing and Artificial Intelligence Journal, vol. 5, no 2.

Schillo M., Fischer K. (2002). Holonic multiagent systems. Manufacturing Systems, vol. 8, no 13, p. 538-550.

Serban A., Yammarino F. J., Dionne S. D., Kahai S. S., Hao C., McHugh K. A. et al. (2015). Leadership emergence in face-to-face and virtual teams: A multi-level model with agentbased simulations, quasi-experimental and experimental tests. The Leadership Quarterly, vol. 26, no 3, p. 402-418.

Uchiya T., Maemura T., Li X., Konno S., Kinoshita T. (2008). Agent interoperability mechanism among heterogeneous agent platforms for symbiotic computing. In Proceedings of the seventh IEEE international conference on cognitive informatics,, p. 286–293. IEEE Computer Society.

Vijver G. Van de. (1997). Emergence et explication. Intellectica, vol. 25, no 2, p. 7-23.

Wood Z., Galton A. (2009). A taxonomy of collective phenomena. Applied Ontology, vol. 4, no 3-4, p. 267-292.

Yoon Y.-J., Lee G.-H., Choi K.-H., Shin D.-R. (2008). Design of agent service system to manage services among heterogeneous multi-agent systems. In Iwsca 2008, ieee international workshop on semantic computing and applications, p. 123–125.