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There are three main aims of this paper. 1- I explain reasons why I awaitlife to lie significantly deeper in chaos than Kauffman approach does, howeverstill in boundary area near `the edge of chaos and order'. The role of negativefeedbacks in stability of living objects is main of those reasons. InKauffman's approach regulation using negative feedbacks is not consideredsufficiently, e.g. in gene regulatory model based on Boolean networks, whichindicates therefore not proper source of stability. Large damage avalanche isavailable only in chaotic phase. It models death in all living objectsnecessary for Darwinian elimination. It is the first step of my approachleading to structural tendencies which are effects of adaptive evolution ofdynamic complex (maturely chaotic) networks. 2- Introduction of s>=2 equallyprobable variants of signal (state of node in Kauffman network) asinterpretively based new statistical mechanism (RSN) instead of the bias p -probability of one of signal variants used in RBN family and RNS. It is alsodifferent than RWN model. For this mechanism which can be treated as veryfrequent, ordered phase occurs only in exceptional cases but for this approachthe chaotic phase is investigated. Annealed approximation expectations andsimulations of damage spreading for different network types (similar to CRBN,FSRBN and EFRBN but with s>=2) are described. Degree of order in chaotic phasein dependency of network parameters and type is discussed. By using such orderlife evolve. 3- A simplified algorithm called `reversed-annealed' forstatistical simulation of damage spreading is described. It is used forsimulations presented in this and next papers describing my approach.

More than two equally probable variants of signal in Kauffman networks as an important overlooked case, negative feedbacks allow life in chaos