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 inAdvances in Practical Applications of Cyber-Physical Multi-Agent Systems: The PAAMS Collection Vol. 10349; pp. 209 - 221
Main Authors Picault, Sébastien, Huang, Yu-Lin, Sicard, Vianney, Beaudeau, François, Ezanno, Pauline
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Switzerland Springer International Publishing AG 01.01.2017
Springer International Publishing
Springer
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN3319599291
9783319599298
3319599305
9783319599304
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-59930-4_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.
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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Keywords Epidemiological modelling
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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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StartPage 209
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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