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| Titel |
Agents, Bayes, and Climatic Risks - a modular modelling approach |
| VerfasserIn |
A. Haas, C. Jaeger |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: Model integration and development of modular modelling systems ; Nr. 4 (2005-08-09), S.3-7 |
| Datensatznummer |
250001398
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| Publikation (Nr.) |
 copernicus.org/adgeo-4-3-2005.pdf |
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| Zusammenfassung |
| When insurance firms, energy companies, governments, NGOs, and other agents
strive to manage climatic risks, it is by no way clear what the aggregate
outcome should and will be. As a framework for investigating this subject, we
present the LAGOM model family. It is based on modules depicting learning
social agents. For managing climate risks, our agents use second order
probabilities and update them by means of a Bayesian mechanism while
differing in priors and risk aversion. The interactions between these modules
and the aggregate outcomes of their actions are implemented using further
modules. The software system is implemented as a series of parallel processes
using the CIAMn approach. It is possible to couple modules irrespective of
the language they are written in, the operating system under which they are
run, and the physical location of the machine. |
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