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A CBP agent for monitoring the carbon dioxide exchange rate from satellite images

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Título:
A CBP agent for monitoring the carbon dioxide exchange rate from satellite images.
Autores: 
Corchado J. M.,J. Bajo and J. Aiken
Libro:
Case-Based Reasoning on Signals and Images. Series Computational Intellignece.

Fecha de Publicación: 
2007

BibTex

@book { book,
title = {A CBP agent for monitoring the carbon dioxide exchange rate from satellite images},
author = {Corchado J. M.,J. Bajo and J. Aiken},
publisher = {Springer Verlag},
series = {Series Computational Intellignece},
year = {2007}
}

XML

<inproceedings key='conf/Corchado/2007' mdate='2007'>
<author>Corchado J. M.</author>
<author>J. Bajo</author>
<author>J. Aiken</author>
<title>A CBP agent for monitoring the carbon dioxide exchange rate from satellite images</title>
<year>2007</year>
<booktitle>Case-Based Reasoning on Signals and Images</booktitle>
</inproceedings>

This work presents a multiagent system for evaluating automatically the interaction
that exists between the atmosphere and the ocean surface. Monitoring and evaluating
within the Ocean CO2 exchange process is a function requiring working with a great
amount of data: satellite images and in-situ vessel’s data. The system presented in this work
focuses on Ambient Intelligence (AmI) technologies since the vision of AmI assumes
seamless, unobtrusive, and often invisible but also controllable interactions between humans
and technology. The work presents the construction of an open multiagent architecture
which, based on the use of deliberative agents incorporating case-based planning
(CBP) systems, offers a distributed model for such an interaction. This work also presents
an analysis and design methodology that facilitates the implementation of CBR agent based
distributed artificial intelligent systems. Moreover, the architecture takes into account the
fact that the working environment is dynamic and therefore it requires autonomous models
that evolve over time. In order to resolve this problem an intelligent environment has been
developed, based on the use of CBP-CBR agents, which are capable of handling several
goals, constructing plans from the data obtained through satellite images and research vessels,
acquiring knowledge and of adapting to environmental changes, are incorporated. The
artificial intelligence system has been successfully tested in the North Atlantic Ocean, and
the results obtained will be presented within this work.

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