Multi-agent system to monitor oceanic environments

The exchange of CO2 between the atmosphere and the ocean surface is a problem that has become increasingly important due to its impact on climatic behavior. Given the large quantity of sources of information available for studying the CO2 problem, it is necessary to provide innovative solutions that facilitate the automation of certain tasks and incorporate decision support systems to obtain a better understanding of this phenomenon. This paper presents a multiagent architecture aimed at providing solutions for monitoring the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carbon dioxide. This process is can be modeled by a multiagent system with advanced learning and adaption capabilities. The proposed multiagent architecture incorporates CBR-agents that integrate novel strategies that both monitor the parameters that affect the interaction, and facilitate the creation of models. The system was tested and this paper presents the results obtained.