A Multi-Level Multi-Agent Simulation Framework in Animal Epidemiology
In order to recommend better control measures in public or animal health, epidemiologists incorporate ever-finer details in their models, from individual diversity to public policies, which often involve several observation scales. Due to the variety of modelling paradigms, it becomes more and more...
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Published in | Advances in Practical Applications of Cyber-Physical Multi-Agent Systems: The PAAMS Collection Vol. 10349; pp. 209 - 221 |
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Main Authors | , , , , |
Format | Book Chapter Conference Proceeding |
Language | English |
Published |
Switzerland
Springer International Publishing AG
01.01.2017
Springer International Publishing Springer |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
ISBN | 3319599291 9783319599298 3319599305 9783319599304 |
ISSN | 0302-9743 1611-3349 |
DOI | 10.1007/978-3-319-59930-4_17 |
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Abstract | In order to recommend better control measures in public or animal health, epidemiologists incorporate ever-finer details in their models, from individual diversity to public policies, which often involve several observation scales. Due to the variety of modelling paradigms, it becomes more and more difficult to compare hypotheses and outcomes, all the more that the increased complexity of simulation programs is not yet counterbalanced by design principles nor by software engineering methods. We propose in this paper to use the multi-level agent-based paradigm to integrate existing methods within a common interface, provide a separation between concerns and reduce the part of code devoted to model designers. We illustrate our approach with an application to the Q fever disease in cattle. |
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AbstractList | In order to recommend better control measures in public or animal health, epidemiologists incorporate ever-finer details in their models, from individual diversity to public policies, which often involve several observation scales. Due to the variety of modelling paradigms, it becomes more and more difficult to compare hypotheses and outcomes, all the more that the increased complexity of simulation programs is not yet counterbalanced by design principles nor by software engineering methods. We propose in this paper to use the multi-level agent-based paradigm to integrate existing methods within a common interface, provide a separation between concerns and reduce the part of code devoted to model designers. We illustrate our approach with an application to the Q fever disease in cattle. In order to recommend better control measures in public or animal health, epidemiologists incorporate ever-finer details in their models, from individual diversity to public policies, which often involve several observation scales. Due to the variety of modelling paradigms, it becomes more and more difficult to compare hypotheses and outcomes, all the more that the increased complexity of simulation programs is not yet counterbalanced by design principles nor by software engineering methods. We propose in this paper to use the multi-level agent-based paradigm to integrate existing methods within a common interface, provide a separation between concerns and reduce the part of code devoted to model designers. We illustrate our approach with an application to the Q fever disease in cattle. |
Author | Ezanno, Pauline Picault, Sébastien Huang, Yu-Lin Sicard, Vianney Beaudeau, François |
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Snippet | In order to recommend better control measures in public or animal health, epidemiologists incorporate ever-finer details in their models, from individual... |
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SubjectTerms | Animal biology Artificial Intelligence Computer Science Epidemiological modelling Knowledge and software engineering Life Sciences Modeling and Simulation Multi-level agent-based simulation Multiagent Systems Veterinary medicine and animal Health |
Title | A Multi-Level Multi-Agent Simulation Framework in Animal Epidemiology |
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