Abstract
This paper presents an architecture that makes it possible to construct dynamic systems capable of growing in dimension and adapting its knowledge to environmental changes. An architecture must define the components of the system (agents in this case), as well as the way in which those components communicate and interact with each other in order to achieve the system’s goals. The work presented here focuses on the development of an agent-based architecture, based on the use of deliberative agents, that incorporate case based reasoning. The proposed architecture requires an analysis and design methodology that facilitates the building of distributed systems using this technology. The proposal combines elements of existing methodologies such as Gaia and AUML in order to take advantage of their characteristics. Moreover the architecture takes into account the possibility of modelling problems in dynamic environments and therefore the use of autonomous models that evolve over time. To solve this problem the architecture incorporates CBR-agents whose aim is to acquire knowledge and adapt themselves to environmental changes. The architecture has been applied to model for evaluating the interaction between the atmosphere and the ocean, as well as for the planification and optimization of sea routes for vessels. The system has been tested successfully, and the results obtained are presented in this paper.
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References
Bauer, B., Huget, M.P.: FIPA Modeling: Agent Class Diagrams (2003)
Bellifime, F., Poggi, A., Rimasa, G.: JADE: a FIPA2000 compliant agent development environement. In: Proceedings of the 5th international conference on autonomous agents, ACM (2001)
Bratman, M.E., Israel, D., Pollack, M.E.: Plans and resource-bounded practical reasoning. Computational Intelligence 4, 349–355 (1988)
Bratman, M.E.: Intentions, Plans and Practical Reason. Harvard University Press, Cambridge (1987)
Corchado, J.M., Laza, R.: Constructing Deliberative Agents with Casebased Reasoning Technology. International Journal of Intelligent Systems 18(12), 1227–1241 (2003)
Corchado, J.M., Lees, B.: A Hybrid Case-based Model for Forecasting. Applied Artificial Intelligence 15(2), 105–127 (2001)
Corchado, J.M., Pavón, J., Corchado, E., Castillo, L.F.: Development of CBR-BDI Agents: A Tourist Guide Application. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 547–559. Springer, Heidelberg (2004)
DeLoach, S.: Anlysis and Design using MaSE and AgentTool. In: Proceedings of the 12th Midwest Artificial Intelligence and Cognitive Science Conference, MAICS (2001)
EURESCOM 2001, MESSAGE: Methodology for engineering systems of software agents. Technical report P907-TI1, EURESCOM (2001)
Glez-Bedia, M., Corchado, J.M.: A planning strategy based on variational calculus for deliberative agents. Computing and Information Systems Journal 10(1), 2–14 (2002) ISBN: 1352-9404
11. Glez-Bedia M., Corchado J. M., Corchado E. S. and Fyfe C. (2002) Analytical
Iglesias, C., Garijo, M., Gonzalez, J.C., Velasco, J.R.: Analysis and Design using MAS-Common KADS. In: Rao, A., Singh, M.P., Wooldridge, M.J. (eds.) ATAL 1997. LNCS, vol. 1365, Springer, Heidelberg (1998)
Lefevre, N., Aiken, J., Rutllant, J., Daneri, G., Lavender, S., Smyth, T.: Observations of pCO2 in the coastal upwelling off Chile: Sapatial and temporal extrapolation using satellite data. Journal of Geophysical research 107 (2002)
Nwana, H.S., Ndumu, D.T., Lee, L.C., Collins, J.C.: ZEUS: A Toolkit for Building Distributed Multi-Agent Systems. Applied Artificial Intelligence Jounal 1(13), 129–185 (1999)
Odell, J., Levy, R., Nodine, M.: FIPA Modeling TC: Agent Class Superstructure Metamodel. FIPA meeting and interim work (2004)
Odell, J., Huget, M.P.: FIPA Modeling: Interaction Diagrams (2003)
Pokahr, A., Braubach, L., Lamersdorf, W.: Jadex: Implementing a BDIInfrastructure for JADE Agents. In: EXP - In Search of Innovation (Special Issue on JADE), Telecom Italia Lab, Turin, Italy, September 2003, vol. 3(3), pp. 76–85 (2003)
Santamaría, J., Nieto, J.: Los agujeros del cambio climático. World Watch no. 12, pp. 62–65 (2000)
Sarmiento, J.L., Dender, M.: Carbon biogeochemistry and climate change. Photosynthesis Research 39, 209–234 (1994)
Takahashi, T., Olafsson, J., Goddard, J.G., Chipman, D.W., Sutherland, S.C.: Seasonal Variation of CO2 and nutrients in the High-latitude surface oceans: a comparative study. Global biochemical Cycles 7(4), 843–878 (1993)
Wooldridge, M., Jennings, N.R.: Agent Theories, Architectures, and Languages: a Survey. In: Wooldridge, Jennings (eds.) Intelligent Agents, pp. 1–22. Springer, Heidelberg (1995)
Wooldridge, M., Jennings, N.R., Kinny, D.: The Gaia Methodology for Agent-Oriented Analysis and Design. Journal of Autonomous Agents and Multi-Agent Systems 3(3), 285–312 (2000)
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Bajo, J., Corchado, J.M. (2006). Multiagent Architecture for Monitoring the North-Atlantic Carbon Dioxide Exchange Rate. In: Marín, R., Onaindía, E., Bugarín, A., Santos, J. (eds) Current Topics in Artificial Intelligence. CAEPIA 2005. Lecture Notes in Computer Science(), vol 4177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881216_34
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DOI: https://doi.org/10.1007/11881216_34
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