  There are three main aims of this paper. 1- I explain reasons why I await
life to lie significantly deeper in chaos than Kauffman approach does, however
still in boundary area near `the edge of chaos and order'. The role of negative
feedbacks in stability of living objects is main of those reasons. In
Kauffman's approach regulation using negative feedbacks is not considered
sufficiently, e.g. in gene regulatory model based on Boolean networks, which
indicates therefore not proper source of stability. Large damage avalanche is
available only in chaotic phase. It models death in all living objects
necessary for Darwinian elimination. It is the first step of my approach
leading to structural tendencies which are effects of adaptive evolution of
dynamic complex (maturely chaotic) networks. 2- Introduction of s>=2 equally
probable variants of signal (state of node in Kauffman network) as
interpretively based new statistical mechanism (RSN) instead of the bias p -
probability of one of signal variants used in RBN family and RNS. It is also
different than RWN model. For this mechanism which can be treated as very
frequent, ordered phase occurs only in exceptional cases but for this approach
the chaotic phase is investigated. Annealed approximation expectations and
simulations of damage spreading for different network types (similar to CRBN,
FSRBN and EFRBN but with s>=2) are described. Degree of order in chaotic phase
in dependency of network parameters and type is discussed. By using such order
life evolve. 3- A simplified algorithm called `reversed-annealed' for
statistical simulation of damage spreading is described. It is used for
simulations presented in this and next papers describing my approach.
