|Hauhs, M; Koch, J; Lange, H: Comparison of time series from ecosystems and an artificial mulit-agent network based on complexity measures, , In Kim, J.T. (Ed.): Systems Biology Workshop, 12 pp., at the VIIIth European Conference on Artificial Life (2005) [Link]|
We investigate ecosystem dynamics by analyzing time series of measured variables. The information content and the complexity of these data are quanti ed by methods from information theory. When applied to runoff (stream discharge) from catchments, the information/complexity relation reveals a simple non-trivial property for a large ensemble (more than 1800) of time series. This behaviour is so far not understood in hydrology. Using a multi-agent network receiving input resembling rainfall and producing output, we are able to reproduce the observed behaviour for the first time. The reconstruction is based on the identification and subsequent replacement of general patterns in the input. We thus consider runoff dynamics as the expression of an interactive learning problem of agents in an ecosystem. Keywords: Artificial life; time series; complexity
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