Measuring the Complexity of Seismicity Pattern Evolution

``Complexity'' has become an ubiquitous term in science. However, there is, much as with ``fractality'', no clear definition of what complexity actually means. Yet, it is important to distinguish between what is merely complicated and what is complex in the sense that simple rules can give rise to very rich behaviour. Seismicity is certainly a complicated phenomenon (difficult to understand) but simple models such as cellular automata indicate that earthquakes are truly complex. From the observational point of view, there exists the problem of quantification of complexity in real world seismicity patterns (in the absence of even a rigid definition of complexity). Such a measurement is desirable, however, not only for fundamental understanding but also for monitoring and possibly for prediction purposes. Maybe the most workable definitions of complexity exist in informatics, summarised under the topic of algorithmic complexity. Here, after introducing the concepts, I apply such measures of complexity to temporally evolving seismicity patterns from different geographic regions. Finally, I discuss the usefulness of the approach and discuss results in view of the occurrence of large earthquakes.