On the invariant sets and chaotic solutions of difference equations with random parameters

We consider the probability model defined by the difference equation
\begin{equation} x_{n+1}=f(\omega_n,x_n), \quad (\omega_n,x_n)\in \Omega\times [a,b], \quad n=0,1,\dots, \tag{1} \end{equation}
where $\Omega$ is a given set with sigma-algebra of subsets $\widetilde{\mathfrak A},$ on which a probability measure $\widetilde \mu$ is defined. Let $\mu $ be a continuation of the measure $\widetilde \mu $ on the sigma-algebra generated by cylindrical sets. We study invariant sets and attractors of the equation with random parameters $(1).$ We receive conditions under which a given set is the maximal attractor. It is shown that, in invariant set $A\subseteq [a,b]$, there can be solutions, which are chaotic with probability one. It is observed in the case when exist an $m_i\in\mathbb N $ and sets $\Omega_i\subset\Omega $ such that $ \mu (\Omega_i)> 0, $ $i=1,2,$ and ${\rm cl}\, f^{m_1}(\Omega_1,A)\cap \,{\rm cl}\, f^{m_2}(\Omega_2,A)=\varnothing.$ It is shown, that solutions, chaotic with probability one, exist also in the case when the equation $(1)$ either has no any cycle, or all cycles are unstable with probability one. The results of the paper are illustrated by the example of a continuous-discrete probabilistic model of the dynamics of an isolated population; for this model we investigate different modes of dynamic development, which have certain differences from the modes of determined models and describe the processes in real physical systems more exhaustively.