Abstract
Ecosystem models are used to interpret and predict the interactions of species and their environment. In this paper, we address the task of inducing ecosystem models from background knowledge and time-series data, and we review IPM, an algorithm that addresses this problem. We demonstrate the system’s ability to construct ecosystem models on two different Earth science data sets. We also compare its behavior with that produced by a more conventional autoregression method. In closing, we discuss related work on model induction and suggest directions for further research on this topic.
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George, D., Saito, K., Langley, P., Bay, S., Arrigo, K.R. (2003). Discovering Ecosystem Models from Time-Series Data. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_13
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DOI: https://doi.org/10.1007/978-3-540-39644-4_13
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