A multi-agent system to learn from oceanic satellite image data

Authors:
Rosa Cano;Angélica González;Juan F. De Paz;Sara Rodríguez
Affiliations:
Departamento Informática y Automática, Universidad de Salamanca, Salamanca, Spain;Departamento Informática y Automática, Universidad de Salamanca, Salamanca, Spain;Departamento Informática y Automática, Universidad de Salamanca, Salamanca, Spain;Departamento Informática y Automática, Universidad de Salamanca, Salamanca, Spain
Venue:
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Year:
2009

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Abstract

This paper presents a multiagent architecture constructed for learning from the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carbon dioxide, and this process is modeled by means of a multiagent system with learning capabilities. The proposed multi-agent architecture incorporates CBR-agents to monitor the parameters that affect the interaction and to facilitate the creation of models. The system has been tested and this paper presents the results obtained.