Abstract
We discuss ways of defining complexity in physics, and in particular for symbol sequences typically arising in autonomous dynamical systems. We stress that complexity should be distinct from randomness. This leads us to consider the difficulty of making optimal forecasts as one (but not the only) suitable measure. This difficulty is discussed in detail for two different examples: left-right symbol sequences of quadratic maps and 0–1 sequences from 1-dimensional cellular automata iterated just one single time. In spite of the seeming triviality of the latter model, we encounter there an extremely rich structure.
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© 1988 Springer-Verlag
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Grassberger, P. (1988). Complexity and forecasting in dynamical systems. In: Peliti, L., Vulpiani, A. (eds) Measures of Complexity. Lecture Notes in Physics, vol 314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-50316-1_1
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DOI: https://doi.org/10.1007/3-540-50316-1_1
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