AGENT-BASED INTERDISCIPLINARY FRAMEWORK FOR DECISION MAKING IN COMPLEX SYSTEMS

Marina V. Sokolova, Antonio Fernández-Caballero, Francisco J. Gómez

2010

Abstract

We offer a framework for the creation of decision support and expert systems for complex natural domains. This is due, on the one hand, to the numerous advantages of intelligent methods of data manipulation and, on the other hand, to the abilities of the computational agents to make decentralized decisions, which are crucial for complex systems modeling and simulation.In our approach, the qualitative improvement in decision making is obtained by using computational agents and interdisciplinary approach. The frameworks combines, on the one hand, the numerous advantages of intelligent methods for data manipulation and, on the other hand, the abilities of the computational agents to make decentralized decisions, which is crucial for complex system modeling and simulation. The approach contributes to decentralization and local decision making within the standard workflow. We demonstrate our framework in a case study and discuss obtained results.

References

  1. Athanasiadis, I. N. and Mitkas, P. A. (2004). An agentbased intelligent environmental monitoring system. CoRR, cs.MA/0407024.
  2. Gorodetski, V. I., Karsaev, O., Samoilov, V., Konushy, V., Mankov, E., and Malyshev, A. (2004). Multi-agent system development kit. In Intelligent Information Processing.
  3. Haykin, S. (1998). Neural Networks: A Comprehensive Foundation. Macmillan, New York.
  4. Karaca, F., Anil, I., Alagha, O., and Camci, F. (2009). Traffic related pm predictor for besiktas, turkey. In Athanasiadis, I. N., Mitkas, P. A., Rizzoli, A. E., and Gómez, J. M., editors, ITEE, pages 317-330. Springer.
  5. Levin, M. S. (2006). Composite Systems Decisions (Decision Engineering). Springer-Verlag New York, Inc., Secaucus, NJ, USA.
  6. Madala, H.R., I. A., editor (1994). Inductive Learning Algorithms for Complex Systems Modelling. CRC Press Inc., Boca Raton, Ann Arbor, London, Tokyo.
  7. Nastar, M. and Wallman, P. (2009). An interdisciplinary approach to resolving conflict in the water domain. In Information Technologies in Environmental Engineering Proceedings of the 4th International ICSC Symposium Thessaloniki, Greece.
  8. Rechtin, E. (1999). Systems architecting of organizations: why eagles can't swim. CRC Press.
  9. Rian˜o, D., Sànchez-Marrè, M., and R.-Roda, I. (2001). Autonomous agents architecture to supervise and control a wastewater treatment plant. In IEA/AIE.
  10. Rotmans, J. (2006). Tools for integrated sustainability assessment: A two-track approach. Integrated Assessment, 6(4).
  11. Sokolova, M. V. and Fernández-Caballero, A. (2007). A multi-agent architecture for environmental impact assessment: Information fusion, data mining and decision making. In ICEIS 2007 - Proceedings of the Ninth International Conference on Enterprise Information Systems, Volume AIDSS, Funchal, Portugal.
  12. Sokolova, M. V. and Fernández-Caballero, A. (2008). Facilitating mas complete life cycle through the protégé- prometheus approach. In Agent and Multi-Agent Systems: Technologies and Applications, KES-AMSTA, Incheon,Korea.
  13. Sokolova, M. V. and Fernández-Caballero, A. (2009). Data mining driven decision making. In ICAART 2009 - Proceedings of the International Conference on Agents and Artificial Intelligence, Porto, Portugal.
  14. Sokolova, M. V. and Fernández-Caballero, A. (2009). Modeling and implementing an agent-based environmental health impact decision support system. Expert Syst. Appl., 36(2):2603-2614.
  15. Terry Bossomaier, Denise Jarratt, M. M. A. T. S. and Thompson, J. (2005). Data integration in agent based modelling. Complexity International, 11.
  16. Urbani, D. and Delhom, M. (2005). Water management policy selection using a decision support system based on a multi-agent system. In AI*IA.
  17. Weiss, G., editor (1999). Multiagent systems: a modern approach to distributed artificial intelligence. MIT Press, Cambridge, MA, USA.
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Paper Citation


in Harvard Style

V. Sokolova M., Fernández-Caballero A. and J. Gómez F. (2010). AGENT-BASED INTERDISCIPLINARY FRAMEWORK FOR DECISION MAKING IN COMPLEX SYSTEMS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-674-022-1, pages 96-103. DOI: 10.5220/0002732000960103


in Bibtex Style

@conference{icaart10,
author={Marina V. Sokolova and Antonio Fernández-Caballero and Francisco J. Gómez},
title={AGENT-BASED INTERDISCIPLINARY FRAMEWORK FOR DECISION MAKING IN COMPLEX SYSTEMS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2010},
pages={96-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002732000960103},
isbn={978-989-674-022-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - AGENT-BASED INTERDISCIPLINARY FRAMEWORK FOR DECISION MAKING IN COMPLEX SYSTEMS
SN - 978-989-674-022-1
AU - V. Sokolova M.
AU - Fernández-Caballero A.
AU - J. Gómez F.
PY - 2010
SP - 96
EP - 103
DO - 10.5220/0002732000960103