Entropy,information and predictability of evolutionary systems

We investigate first several entropy concepts, from static to dynamic entropy. Dynamic entropy is introduced as a measure of predictability. Then the relation between entropy and information is studied. Following Wiener information is considered as a non‐physical quantity, not matter or energy. Information is understood as a binary relation between a sender and a receiver. We differentiate between bound and free information. Information can be created by selforganization, historically it is connected with the origin of life. The structure and predictability of informational strings is investigated. For example we study symbolic sequences generated by evolution, as e.g. texts. It is shown that several information carriers show criticality connected with the existence of long‐range correlations, long memory in time and historical behaviour (self‐tuned criticality). The higher order Shannon entropies and the conditional entropies (dynamical entropies and there limit) are calculated, characteristic scaling laws are found.