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is this information?”. In this case, interactions may be hidden from the observation, in many cases simply a string of bits or characters, without direct reference to the process that produced it. For this purpose, complexity can be seen as the amount of information required to describe a phenomenon at a particular scale (Bar-Yam, 2004b). If more information is required, then the complexity can be said to be higher. However, the scale of observation is very important. For example, the information of the string ’1010101010’ is maximal at a 1-bit scale (base 2), while it is minimal at a 2-bit scale (base 4) ’22222’. 

Several measures of complexity assume that highly ordered strings ( I ≈ 0) are not com- plex, while strings with a high information value ( I ≈ 1) have a high complexity. In some cases, this makes sense, but in others, it implies that random or chaotic systems have the highest complexity. Several other measures—such as effective complexity (Gell-Mann and Lloyd, 1996), Langton’s λ (Langton, 1990) and Wuensche’s Z (Wuensche, 1999)—see com- plexity as a balance between ordered and chaotic dynamics. In this direction, the measure proposed by L´ opez-Ruiz et al. (1995) is interesting, since they measure complexity as the 

